Upload folder using huggingface_hub

.gitattributes

@@ -33,3 +33,9 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+checkpoint-200/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+checkpoint-400/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+checkpoint-600/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+checkpoint-800/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+checkpoint-879/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,209 @@
+---
+base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.20.0

adapter_config.json

@@ -0,0 +1,50 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "monteclora_config": null,
+  "peft_type": "LORA",
+  "peft_version": "0.20.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "up_proj",
+    "down_proj",
+    "k_proj",
+    "o_proj",
+    "v_proj",
+    "gate_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false,
+  "velora_config": null
+}

adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8de8bf2fd18381ef12444c3a4498a621e7212eb593668a78afcdd21768f5b0fa
+size 73911112

checkpoint-200/README.md

@@ -0,0 +1,209 @@
+---
+base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.20.0

checkpoint-200/adapter_config.json

@@ -0,0 +1,50 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "monteclora_config": null,
+  "peft_type": "LORA",
+  "peft_version": "0.20.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "up_proj",
+    "down_proj",
+    "k_proj",
+    "o_proj",
+    "v_proj",
+    "gate_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false,
+  "velora_config": null
+}

checkpoint-200/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cb7df524a13f132acd4e14dd36411982f44552153da805f36658baba203ef6ec
+size 73911112

checkpoint-200/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8ad9065bb4340c236a62d7ec1fc12f7c4678de00c0244cc25bc0c4ba5ea10138
+size 37969268

checkpoint-200/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fbd5dc3846fde0a8e01887b93f1b5753679875cb16005c0f2219d5be2fb0f717
+size 14244

checkpoint-200/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5f0a841d0fa965ade7dbf3a34a1021756a215f73311c59e711208417d012e806
+size 1064

checkpoint-200/special_tokens_map.json

@@ -0,0 +1,17 @@
+{
+  "bos_token": {
+    "content": "<｜begin▁of▁sentence｜>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<｜end▁of▁sentence｜>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<｜end▁of▁sentence｜>"
+}

checkpoint-200/tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e20ddafc659ba90242154b55275402edeca0715e5dbb30f56815a4ce081f4893
+size 11422778

checkpoint-200/tokenizer_config.json

@@ -0,0 +1,194 @@
+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "add_prefix_space": null,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<｜end▁of▁sentence｜>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<｜User｜>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151645": {
+      "content": "<｜Assistant｜>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151646": {
+      "content": "<｜begin▁of▁sentence｜>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|EOT|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151648": {
+      "content": "<think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151649": {
+      "content": "</think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "bos_token": "<｜begin▁of▁sentence｜>",
+  "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<｜User｜>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<｜Assistant｜><｜tool▁calls▁begin｜><｜tool▁call▁begin��>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{%- set ns.is_first = true -%}{%- else %}{{'\\n' + '<｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{{'<｜tool▁calls▁end｜><｜end▁of▁sentence｜>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<｜tool▁outputs▁end｜>' + message['content'] + '<｜end▁of▁sentence｜>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<｜Assistant｜>' + content + '<｜end▁of▁sentence｜>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<｜tool▁outputs▁begin｜><｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\\n<｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<｜tool▁outputs▁end｜>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<｜Assistant｜><think>\\n'}}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<｜end▁of▁sentence｜>",
+  "legacy": true,
+  "model_max_length": 16384,
+  "pad_token": "<｜end▁of▁sentence｜>",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": null,
+  "use_default_system_prompt": false
+}

checkpoint-200/trainer_state.json

@@ -0,0 +1,393 @@
+{
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 0.6811409110259685,
+  "eval_steps": 500,
+  "global_step": 200,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.017028522775649212,
+      "grad_norm": 2.3286359310150146,
+      "learning_rate": 0.0001988623435722412,
+      "loss": 4.1641,
+      "mean_token_accuracy": 0.3866006717085838,
+      "num_tokens": 4326.0,
+      "step": 5
+    },
+    {
+      "epoch": 0.034057045551298425,
+      "grad_norm": 1.4926602840423584,
+      "learning_rate": 0.00019772468714448238,
+      "loss": 2.0591,
+      "mean_token_accuracy": 0.6790341928601265,
+      "num_tokens": 8676.0,
+      "step": 10
+    },
+    {
+      "epoch": 0.05108556832694764,
+      "grad_norm": 1.0835968255996704,
+      "learning_rate": 0.00019658703071672356,
+      "loss": 1.3145,
+      "mean_token_accuracy": 0.8256841972470284,
+      "num_tokens": 12796.0,
+      "step": 15
+    },
+    {
+      "epoch": 0.06811409110259685,
+      "grad_norm": 0.7724414467811584,
+      "learning_rate": 0.00019544937428896475,
+      "loss": 1.3324,
+      "mean_token_accuracy": 0.8117582932114601,
+      "num_tokens": 17119.0,
+      "step": 20
+    },
+    {
+      "epoch": 0.08514261387824607,
+      "grad_norm": 0.785762369632721,
+      "learning_rate": 0.00019431171786120593,
+      "loss": 1.3375,
+      "mean_token_accuracy": 0.8029867172241211,
+      "num_tokens": 21499.0,
+      "step": 25
+    },
+    {
+      "epoch": 0.10217113665389528,
+      "grad_norm": 0.6702725291252136,
+      "learning_rate": 0.00019317406143344712,
+      "loss": 1.2159,
+      "mean_token_accuracy": 0.8230627462267875,
+      "num_tokens": 25785.0,
+      "step": 30
+    },
+    {
+      "epoch": 0.11919965942954448,
+      "grad_norm": 0.6287369728088379,
+      "learning_rate": 0.0001920364050056883,
+      "loss": 1.1634,
+      "mean_token_accuracy": 0.8315445825457572,
+      "num_tokens": 29980.0,
+      "step": 35
+    },
+    {
+      "epoch": 0.1362281822051937,
+      "grad_norm": 0.6573143005371094,
+      "learning_rate": 0.00019089874857792946,
+      "loss": 1.3762,
+      "mean_token_accuracy": 0.7971536681056023,
+      "num_tokens": 34497.0,
+      "step": 40
+    },
+    {
+      "epoch": 0.1532567049808429,
+      "grad_norm": 0.6560688614845276,
+      "learning_rate": 0.00018976109215017067,
+      "loss": 1.1589,
+      "mean_token_accuracy": 0.8251897826790809,
+      "num_tokens": 38800.0,
+      "step": 45
+    },
+    {
+      "epoch": 0.17028522775649213,
+      "grad_norm": 0.6654791831970215,
+      "learning_rate": 0.00018862343572241183,
+      "loss": 1.1498,
+      "mean_token_accuracy": 0.8319168403744698,
+      "num_tokens": 43055.0,
+      "step": 50
+    },
+    {
+      "epoch": 0.18731375053214133,
+      "grad_norm": 0.7387417554855347,
+      "learning_rate": 0.00018748577929465302,
+      "loss": 1.1265,
+      "mean_token_accuracy": 0.8290244281291962,
+      "num_tokens": 47346.0,
+      "step": 55
+    },
+    {
+      "epoch": 0.20434227330779056,
+      "grad_norm": 0.5795997977256775,
+      "learning_rate": 0.0001863481228668942,
+      "loss": 1.0046,
+      "mean_token_accuracy": 0.8534704640507698,
+      "num_tokens": 51485.0,
+      "step": 60
+    },
+    {
+      "epoch": 0.22137079608343976,
+      "grad_norm": 0.6834130883216858,
+      "learning_rate": 0.0001852104664391354,
+      "loss": 1.113,
+      "mean_token_accuracy": 0.8345914751291275,
+      "num_tokens": 55716.0,
+      "step": 65
+    },
+    {
+      "epoch": 0.23839931885908897,
+      "grad_norm": 0.7211284041404724,
+      "learning_rate": 0.00018407281001137657,
+      "loss": 1.2132,
+      "mean_token_accuracy": 0.8207321017980576,
+      "num_tokens": 60030.0,
+      "step": 70
+    },
+    {
+      "epoch": 0.2554278416347382,
+      "grad_norm": 0.6312271356582642,
+      "learning_rate": 0.00018293515358361776,
+      "loss": 1.0987,
+      "mean_token_accuracy": 0.8333725541830063,
+      "num_tokens": 64288.0,
+      "step": 75
+    },
+    {
+      "epoch": 0.2724563644103874,
+      "grad_norm": 0.7119404077529907,
+      "learning_rate": 0.00018179749715585894,
+      "loss": 1.0981,
+      "mean_token_accuracy": 0.8323698997497558,
+      "num_tokens": 68548.0,
+      "step": 80
+    },
+    {
+      "epoch": 0.2894848871860366,
+      "grad_norm": 0.9000201225280762,
+      "learning_rate": 0.00018065984072810013,
+      "loss": 1.146,
+      "mean_token_accuracy": 0.8253335595130921,
+      "num_tokens": 72914.0,
+      "step": 85
+    },
+    {
+      "epoch": 0.3065134099616858,
+      "grad_norm": 0.6050537824630737,
+      "learning_rate": 0.0001795221843003413,
+      "loss": 1.0111,
+      "mean_token_accuracy": 0.842674246430397,
+      "num_tokens": 77168.0,
+      "step": 90
+    },
+    {
+      "epoch": 0.32354193273733506,
+      "grad_norm": 0.684512197971344,
+      "learning_rate": 0.0001783845278725825,
+      "loss": 1.1186,
+      "mean_token_accuracy": 0.8351956441998482,
+      "num_tokens": 81439.0,
+      "step": 95
+    },
+    {
+      "epoch": 0.34057045551298426,
+      "grad_norm": 0.7323129773139954,
+      "learning_rate": 0.00017724687144482368,
+      "loss": 1.1287,
+      "mean_token_accuracy": 0.8245970487594605,
+      "num_tokens": 85773.0,
+      "step": 100
+    },
+    {
+      "epoch": 0.35759897828863346,
+      "grad_norm": 0.7547741532325745,
+      "learning_rate": 0.00017610921501706487,
+      "loss": 1.0868,
+      "mean_token_accuracy": 0.8298466548323631,
+      "num_tokens": 90117.0,
+      "step": 105
+    },
+    {
+      "epoch": 0.37462750106428266,
+      "grad_norm": 0.7113769054412842,
+      "learning_rate": 0.00017497155858930602,
+      "loss": 1.1214,
+      "mean_token_accuracy": 0.8299670115113258,
+      "num_tokens": 94412.0,
+      "step": 110
+    },
+    {
+      "epoch": 0.39165602383993187,
+      "grad_norm": 0.7486220002174377,
+      "learning_rate": 0.00017383390216154724,
+      "loss": 1.1452,
+      "mean_token_accuracy": 0.8283886179327965,
+      "num_tokens": 98782.0,
+      "step": 115
+    },
+    {
+      "epoch": 0.4086845466155811,
+      "grad_norm": 0.658633828163147,
+      "learning_rate": 0.0001726962457337884,
+      "loss": 1.0415,
+      "mean_token_accuracy": 0.8431179687380791,
+      "num_tokens": 103011.0,
+      "step": 120
+    },
+    {
+      "epoch": 0.4257130693912303,
+      "grad_norm": 0.783794105052948,
+      "learning_rate": 0.0001715585893060296,
+      "loss": 1.1056,
+      "mean_token_accuracy": 0.8254878520965576,
+      "num_tokens": 107402.0,
+      "step": 125
+    },
+    {
+      "epoch": 0.4427415921668795,
+      "grad_norm": 0.7954565286636353,
+      "learning_rate": 0.00017042093287827076,
+      "loss": 1.0518,
+      "mean_token_accuracy": 0.8375606715679169,
+      "num_tokens": 111707.0,
+      "step": 130
+    },
+    {
+      "epoch": 0.45977011494252873,
+      "grad_norm": 0.6913949847221375,
+      "learning_rate": 0.00016928327645051198,
+      "loss": 1.1104,
+      "mean_token_accuracy": 0.8326424166560173,
+      "num_tokens": 115998.0,
+      "step": 135
+    },
+    {
+      "epoch": 0.47679863771817793,
+      "grad_norm": 0.7918037176132202,
+      "learning_rate": 0.00016814562002275313,
+      "loss": 1.0495,
+      "mean_token_accuracy": 0.8390962019562721,
+      "num_tokens": 120271.0,
+      "step": 140
+    },
+    {
+      "epoch": 0.49382716049382713,
+      "grad_norm": 0.7816826701164246,
+      "learning_rate": 0.00016700796359499432,
+      "loss": 1.0463,
+      "mean_token_accuracy": 0.8433194428682327,
+      "num_tokens": 124461.0,
+      "step": 145
+    },
+    {
+      "epoch": 0.5108556832694764,
+      "grad_norm": 0.8069042563438416,
+      "learning_rate": 0.0001658703071672355,
+      "loss": 1.0664,
+      "mean_token_accuracy": 0.8278923153877258,
+      "num_tokens": 128781.0,
+      "step": 150
+    },
+    {
+      "epoch": 0.5278842060451255,
+      "grad_norm": 1.0114731788635254,
+      "learning_rate": 0.0001647326507394767,
+      "loss": 1.1217,
+      "mean_token_accuracy": 0.8267972275614739,
+      "num_tokens": 133167.0,
+      "step": 155
+    },
+    {
+      "epoch": 0.5449127288207748,
+      "grad_norm": 0.7900378704071045,
+      "learning_rate": 0.00016359499431171787,
+      "loss": 0.971,
+      "mean_token_accuracy": 0.8421565622091294,
+      "num_tokens": 137464.0,
+      "step": 160
+    },
+    {
+      "epoch": 0.561941251596424,
+      "grad_norm": 0.8059927821159363,
+      "learning_rate": 0.00016245733788395906,
+      "loss": 1.0457,
+      "mean_token_accuracy": 0.8381335601210594,
+      "num_tokens": 141760.0,
+      "step": 165
+    },
+    {
+      "epoch": 0.5789697743720732,
+      "grad_norm": 0.7589371800422668,
+      "learning_rate": 0.00016131968145620024,
+      "loss": 1.0208,
+      "mean_token_accuracy": 0.8342296928167343,
+      "num_tokens": 146051.0,
+      "step": 170
+    },
+    {
+      "epoch": 0.5959982971477225,
+      "grad_norm": 0.692416250705719,
+      "learning_rate": 0.00016018202502844143,
+      "loss": 0.9837,
+      "mean_token_accuracy": 0.8510025009512902,
+      "num_tokens": 150270.0,
+      "step": 175
+    },
+    {
+      "epoch": 0.6130268199233716,
+      "grad_norm": 0.6662923097610474,
+      "learning_rate": 0.0001590443686006826,
+      "loss": 0.9835,
+      "mean_token_accuracy": 0.8463438332080842,
+      "num_tokens": 154537.0,
+      "step": 180
+    },
+    {
+      "epoch": 0.6300553426990209,
+      "grad_norm": 0.7452691793441772,
+      "learning_rate": 0.0001579067121729238,
+      "loss": 1.0496,
+      "mean_token_accuracy": 0.8375737622380257,
+      "num_tokens": 158810.0,
+      "step": 185
+    },
+    {
+      "epoch": 0.6470838654746701,
+      "grad_norm": 0.809700608253479,
+      "learning_rate": 0.00015676905574516496,
+      "loss": 1.0595,
+      "mean_token_accuracy": 0.8294038504362107,
+      "num_tokens": 163213.0,
+      "step": 190
+    },
+    {
+      "epoch": 0.6641123882503193,
+      "grad_norm": 0.7708745002746582,
+      "learning_rate": 0.00015563139931740617,
+      "loss": 1.0976,
+      "mean_token_accuracy": 0.8289313957095146,
+      "num_tokens": 167607.0,
+      "step": 195
+    },
+    {
+      "epoch": 0.6811409110259685,
+      "grad_norm": 0.6482141613960266,
+      "learning_rate": 0.00015449374288964733,
+      "loss": 1.0701,
+      "mean_token_accuracy": 0.8261386752128601,
+      "num_tokens": 172024.0,
+      "step": 200
+    }
+  ],
+  "logging_steps": 5,
+  "max_steps": 879,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 3,
+  "save_steps": 200,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 1612393756090368.0,
+  "train_batch_size": 1,
+  "trial_name": null,
+  "trial_params": null
+}

checkpoint-200/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:001de43419a04313fd3d652571d90911489fbcebf2f0e7c3f8aa624286dfc855
+size 5624

checkpoint-400/README.md

@@ -0,0 +1,209 @@
+---
+base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.20.0

checkpoint-400/adapter_config.json

@@ -0,0 +1,50 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "monteclora_config": null,
+  "peft_type": "LORA",
+  "peft_version": "0.20.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "up_proj",
+    "down_proj",
+    "k_proj",
+    "o_proj",
+    "v_proj",
+    "gate_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false,
+  "velora_config": null
+}

checkpoint-400/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:71ac0ee7f7bbd14b6f156757d2e936048b87875596ffc471cfa5e817bbd96942
+size 73911112

checkpoint-400/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:19f063558cb0368749b80f6045392123df659ff5c089159e50672040f61f19a3
+size 37969652

checkpoint-400/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:36af5667dfbe01f624b0c26ca62afba73c7149bbea27ed1ff6944191087a2212
+size 14244

checkpoint-400/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fbaa767a1867f6f8022ea209ef1a03a369e44768800ec83f2966bcd9939650bb
+size 1064

checkpoint-400/special_tokens_map.json

@@ -0,0 +1,17 @@
+{
+  "bos_token": {
+    "content": "<｜begin▁of▁sentence｜>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<｜end▁of▁sentence｜>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<｜end▁of▁sentence｜>"
+}

checkpoint-400/tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e20ddafc659ba90242154b55275402edeca0715e5dbb30f56815a4ce081f4893
+size 11422778

checkpoint-400/tokenizer_config.json

@@ -0,0 +1,194 @@
+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "add_prefix_space": null,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<｜end▁of▁sentence｜>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<｜User｜>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151645": {
+      "content": "<｜Assistant｜>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151646": {
+      "content": "<｜begin▁of▁sentence｜>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|EOT|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151648": {
+      "content": "<think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151649": {
+      "content": "</think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "bos_token": "<｜begin▁of▁sentence｜>",
+  "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<｜User｜>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<｜Assistant｜><｜tool▁calls▁begin｜><｜tool▁call▁begin��>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{%- set ns.is_first = true -%}{%- else %}{{'\\n' + '<｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{{'<｜tool▁calls▁end｜><｜end▁of▁sentence｜>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<｜tool▁outputs▁end｜>' + message['content'] + '<｜end▁of▁sentence｜>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<｜Assistant｜>' + content + '<｜end▁of▁sentence｜>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<｜tool▁outputs▁begin｜><｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\\n<｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<｜tool▁outputs▁end｜>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<｜Assistant｜><think>\\n'}}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<｜end▁of▁sentence｜>",
+  "legacy": true,
+  "model_max_length": 16384,
+  "pad_token": "<｜end▁of▁sentence｜>",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": null,
+  "use_default_system_prompt": false
+}

checkpoint-400/trainer_state.json

@@ -0,0 +1,753 @@
+{
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 1.362281822051937,
+  "eval_steps": 500,
+  "global_step": 400,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.017028522775649212,
+      "grad_norm": 2.3286359310150146,
+      "learning_rate": 0.0001988623435722412,
+      "loss": 4.1641,
+      "mean_token_accuracy": 0.3866006717085838,
+      "num_tokens": 4326.0,
+      "step": 5
+    },
+    {
+      "epoch": 0.034057045551298425,
+      "grad_norm": 1.4926602840423584,
+      "learning_rate": 0.00019772468714448238,
+      "loss": 2.0591,
+      "mean_token_accuracy": 0.6790341928601265,
+      "num_tokens": 8676.0,
+      "step": 10
+    },
+    {
+      "epoch": 0.05108556832694764,
+      "grad_norm": 1.0835968255996704,
+      "learning_rate": 0.00019658703071672356,
+      "loss": 1.3145,
+      "mean_token_accuracy": 0.8256841972470284,
+      "num_tokens": 12796.0,
+      "step": 15
+    },
+    {
+      "epoch": 0.06811409110259685,
+      "grad_norm": 0.7724414467811584,
+      "learning_rate": 0.00019544937428896475,
+      "loss": 1.3324,
+      "mean_token_accuracy": 0.8117582932114601,
+      "num_tokens": 17119.0,
+      "step": 20
+    },
+    {
+      "epoch": 0.08514261387824607,
+      "grad_norm": 0.785762369632721,
+      "learning_rate": 0.00019431171786120593,
+      "loss": 1.3375,
+      "mean_token_accuracy": 0.8029867172241211,
+      "num_tokens": 21499.0,
+      "step": 25
+    },
+    {
+      "epoch": 0.10217113665389528,
+      "grad_norm": 0.6702725291252136,
+      "learning_rate": 0.00019317406143344712,
+      "loss": 1.2159,
+      "mean_token_accuracy": 0.8230627462267875,
+      "num_tokens": 25785.0,
+      "step": 30
+    },
+    {
+      "epoch": 0.11919965942954448,
+      "grad_norm": 0.6287369728088379,
+      "learning_rate": 0.0001920364050056883,
+      "loss": 1.1634,
+      "mean_token_accuracy": 0.8315445825457572,
+      "num_tokens": 29980.0,
+      "step": 35
+    },
+    {
+      "epoch": 0.1362281822051937,
+      "grad_norm": 0.6573143005371094,
+      "learning_rate": 0.00019089874857792946,
+      "loss": 1.3762,
+      "mean_token_accuracy": 0.7971536681056023,
+      "num_tokens": 34497.0,
+      "step": 40
+    },
+    {
+      "epoch": 0.1532567049808429,
+      "grad_norm": 0.6560688614845276,
+      "learning_rate": 0.00018976109215017067,
+      "loss": 1.1589,
+      "mean_token_accuracy": 0.8251897826790809,
+      "num_tokens": 38800.0,
+      "step": 45
+    },
+    {
+      "epoch": 0.17028522775649213,
+      "grad_norm": 0.6654791831970215,
+      "learning_rate": 0.00018862343572241183,
+      "loss": 1.1498,
+      "mean_token_accuracy": 0.8319168403744698,
+      "num_tokens": 43055.0,
+      "step": 50
+    },
+    {
+      "epoch": 0.18731375053214133,
+      "grad_norm": 0.7387417554855347,
+      "learning_rate": 0.00018748577929465302,
+      "loss": 1.1265,
+      "mean_token_accuracy": 0.8290244281291962,
+      "num_tokens": 47346.0,
+      "step": 55
+    },
+    {
+      "epoch": 0.20434227330779056,
+      "grad_norm": 0.5795997977256775,
+      "learning_rate": 0.0001863481228668942,
+      "loss": 1.0046,
+      "mean_token_accuracy": 0.8534704640507698,
+      "num_tokens": 51485.0,
+      "step": 60
+    },
+    {
+      "epoch": 0.22137079608343976,
+      "grad_norm": 0.6834130883216858,
+      "learning_rate": 0.0001852104664391354,
+      "loss": 1.113,
+      "mean_token_accuracy": 0.8345914751291275,
+      "num_tokens": 55716.0,
+      "step": 65
+    },
+    {
+      "epoch": 0.23839931885908897,
+      "grad_norm": 0.7211284041404724,
+      "learning_rate": 0.00018407281001137657,
+      "loss": 1.2132,
+      "mean_token_accuracy": 0.8207321017980576,
+      "num_tokens": 60030.0,
+      "step": 70
+    },
+    {
+      "epoch": 0.2554278416347382,
+      "grad_norm": 0.6312271356582642,
+      "learning_rate": 0.00018293515358361776,
+      "loss": 1.0987,
+      "mean_token_accuracy": 0.8333725541830063,
+      "num_tokens": 64288.0,
+      "step": 75
+    },
+    {
+      "epoch": 0.2724563644103874,
+      "grad_norm": 0.7119404077529907,
+      "learning_rate": 0.00018179749715585894,
+      "loss": 1.0981,
+      "mean_token_accuracy": 0.8323698997497558,
+      "num_tokens": 68548.0,
+      "step": 80
+    },
+    {
+      "epoch": 0.2894848871860366,
+      "grad_norm": 0.9000201225280762,
+      "learning_rate": 0.00018065984072810013,
+      "loss": 1.146,
+      "mean_token_accuracy": 0.8253335595130921,
+      "num_tokens": 72914.0,
+      "step": 85
+    },
+    {
+      "epoch": 0.3065134099616858,
+      "grad_norm": 0.6050537824630737,
+      "learning_rate": 0.0001795221843003413,
+      "loss": 1.0111,
+      "mean_token_accuracy": 0.842674246430397,
+      "num_tokens": 77168.0,
+      "step": 90
+    },
+    {
+      "epoch": 0.32354193273733506,
+      "grad_norm": 0.684512197971344,
+      "learning_rate": 0.0001783845278725825,
+      "loss": 1.1186,
+      "mean_token_accuracy": 0.8351956441998482,
+      "num_tokens": 81439.0,
+      "step": 95
+    },
+    {
+      "epoch": 0.34057045551298426,
+      "grad_norm": 0.7323129773139954,
+      "learning_rate": 0.00017724687144482368,
+      "loss": 1.1287,
+      "mean_token_accuracy": 0.8245970487594605,
+      "num_tokens": 85773.0,
+      "step": 100
+    },
+    {
+      "epoch": 0.35759897828863346,
+      "grad_norm": 0.7547741532325745,
+      "learning_rate": 0.00017610921501706487,
+      "loss": 1.0868,
+      "mean_token_accuracy": 0.8298466548323631,
+      "num_tokens": 90117.0,
+      "step": 105
+    },
+    {
+      "epoch": 0.37462750106428266,
+      "grad_norm": 0.7113769054412842,
+      "learning_rate": 0.00017497155858930602,
+      "loss": 1.1214,
+      "mean_token_accuracy": 0.8299670115113258,
+      "num_tokens": 94412.0,
+      "step": 110
+    },
+    {
+      "epoch": 0.39165602383993187,
+      "grad_norm": 0.7486220002174377,
+      "learning_rate": 0.00017383390216154724,
+      "loss": 1.1452,
+      "mean_token_accuracy": 0.8283886179327965,
+      "num_tokens": 98782.0,
+      "step": 115
+    },
+    {
+      "epoch": 0.4086845466155811,
+      "grad_norm": 0.658633828163147,
+      "learning_rate": 0.0001726962457337884,
+      "loss": 1.0415,
+      "mean_token_accuracy": 0.8431179687380791,
+      "num_tokens": 103011.0,
+      "step": 120
+    },
+    {
+      "epoch": 0.4257130693912303,
+      "grad_norm": 0.783794105052948,
+      "learning_rate": 0.0001715585893060296,
+      "loss": 1.1056,
+      "mean_token_accuracy": 0.8254878520965576,
+      "num_tokens": 107402.0,
+      "step": 125
+    },
+    {
+      "epoch": 0.4427415921668795,
+      "grad_norm": 0.7954565286636353,
+      "learning_rate": 0.00017042093287827076,
+      "loss": 1.0518,
+      "mean_token_accuracy": 0.8375606715679169,
+      "num_tokens": 111707.0,
+      "step": 130
+    },
+    {
+      "epoch": 0.45977011494252873,
+      "grad_norm": 0.6913949847221375,
+      "learning_rate": 0.00016928327645051198,
+      "loss": 1.1104,
+      "mean_token_accuracy": 0.8326424166560173,
+      "num_tokens": 115998.0,
+      "step": 135
+    },
+    {
+      "epoch": 0.47679863771817793,
+      "grad_norm": 0.7918037176132202,
+      "learning_rate": 0.00016814562002275313,
+      "loss": 1.0495,
+      "mean_token_accuracy": 0.8390962019562721,
+      "num_tokens": 120271.0,
+      "step": 140
+    },
+    {
+      "epoch": 0.49382716049382713,
+      "grad_norm": 0.7816826701164246,
+      "learning_rate": 0.00016700796359499432,
+      "loss": 1.0463,
+      "mean_token_accuracy": 0.8433194428682327,
+      "num_tokens": 124461.0,
+      "step": 145
+    },
+    {
+      "epoch": 0.5108556832694764,
+      "grad_norm": 0.8069042563438416,
+      "learning_rate": 0.0001658703071672355,
+      "loss": 1.0664,
+      "mean_token_accuracy": 0.8278923153877258,
+      "num_tokens": 128781.0,
+      "step": 150
+    },
+    {
+      "epoch": 0.5278842060451255,
+      "grad_norm": 1.0114731788635254,
+      "learning_rate": 0.0001647326507394767,
+      "loss": 1.1217,
+      "mean_token_accuracy": 0.8267972275614739,
+      "num_tokens": 133167.0,
+      "step": 155
+    },
+    {
+      "epoch": 0.5449127288207748,
+      "grad_norm": 0.7900378704071045,
+      "learning_rate": 0.00016359499431171787,
+      "loss": 0.971,
+      "mean_token_accuracy": 0.8421565622091294,
+      "num_tokens": 137464.0,
+      "step": 160
+    },
+    {
+      "epoch": 0.561941251596424,
+      "grad_norm": 0.8059927821159363,
+      "learning_rate": 0.00016245733788395906,
+      "loss": 1.0457,
+      "mean_token_accuracy": 0.8381335601210594,
+      "num_tokens": 141760.0,
+      "step": 165
+    },
+    {
+      "epoch": 0.5789697743720732,
+      "grad_norm": 0.7589371800422668,
+      "learning_rate": 0.00016131968145620024,
+      "loss": 1.0208,
+      "mean_token_accuracy": 0.8342296928167343,
+      "num_tokens": 146051.0,
+      "step": 170
+    },
+    {
+      "epoch": 0.5959982971477225,
+      "grad_norm": 0.692416250705719,
+      "learning_rate": 0.00016018202502844143,
+      "loss": 0.9837,
+      "mean_token_accuracy": 0.8510025009512902,
+      "num_tokens": 150270.0,
+      "step": 175
+    },
+    {
+      "epoch": 0.6130268199233716,
+      "grad_norm": 0.6662923097610474,
+      "learning_rate": 0.0001590443686006826,
+      "loss": 0.9835,
+      "mean_token_accuracy": 0.8463438332080842,
+      "num_tokens": 154537.0,
+      "step": 180
+    },
+    {
+      "epoch": 0.6300553426990209,
+      "grad_norm": 0.7452691793441772,
+      "learning_rate": 0.0001579067121729238,
+      "loss": 1.0496,
+      "mean_token_accuracy": 0.8375737622380257,
+      "num_tokens": 158810.0,
+      "step": 185
+    },
+    {
+      "epoch": 0.6470838654746701,
+      "grad_norm": 0.809700608253479,
+      "learning_rate": 0.00015676905574516496,
+      "loss": 1.0595,
+      "mean_token_accuracy": 0.8294038504362107,
+      "num_tokens": 163213.0,
+      "step": 190
+    },
+    {
+      "epoch": 0.6641123882503193,
+      "grad_norm": 0.7708745002746582,
+      "learning_rate": 0.00015563139931740617,
+      "loss": 1.0976,
+      "mean_token_accuracy": 0.8289313957095146,
+      "num_tokens": 167607.0,
+      "step": 195
+    },
+    {
+      "epoch": 0.6811409110259685,
+      "grad_norm": 0.6482141613960266,
+      "learning_rate": 0.00015449374288964733,
+      "loss": 1.0701,
+      "mean_token_accuracy": 0.8261386752128601,
+      "num_tokens": 172024.0,
+      "step": 200
+    },
+    {
+      "epoch": 0.6981694338016177,
+      "grad_norm": 0.7164883613586426,
+      "learning_rate": 0.00015335608646188854,
+      "loss": 0.9878,
+      "mean_token_accuracy": 0.8418964132666588,
+      "num_tokens": 176317.0,
+      "step": 205
+    },
+    {
+      "epoch": 0.7151979565772669,
+      "grad_norm": 0.710343599319458,
+      "learning_rate": 0.0001522184300341297,
+      "loss": 0.9306,
+      "mean_token_accuracy": 0.8468034327030182,
+      "num_tokens": 180558.0,
+      "step": 210
+    },
+    {
+      "epoch": 0.7322264793529162,
+      "grad_norm": 0.863784909248352,
+      "learning_rate": 0.00015108077360637088,
+      "loss": 1.0544,
+      "mean_token_accuracy": 0.8359945684671402,
+      "num_tokens": 184885.0,
+      "step": 215
+    },
+    {
+      "epoch": 0.7492550021285653,
+      "grad_norm": 0.8381637930870056,
+      "learning_rate": 0.00014994311717861207,
+      "loss": 1.0522,
+      "mean_token_accuracy": 0.836811026930809,
+      "num_tokens": 189219.0,
+      "step": 220
+    },
+    {
+      "epoch": 0.7662835249042146,
+      "grad_norm": 0.683501124382019,
+      "learning_rate": 0.00014880546075085325,
+      "loss": 0.9427,
+      "mean_token_accuracy": 0.8544979348778725,
+      "num_tokens": 193437.0,
+      "step": 225
+    },
+    {
+      "epoch": 0.7833120476798637,
+      "grad_norm": 0.7609812617301941,
+      "learning_rate": 0.00014766780432309444,
+      "loss": 1.0048,
+      "mean_token_accuracy": 0.8403829500079155,
+      "num_tokens": 197724.0,
+      "step": 230
+    },
+    {
+      "epoch": 0.800340570455513,
+      "grad_norm": 0.8223949074745178,
+      "learning_rate": 0.00014653014789533562,
+      "loss": 1.078,
+      "mean_token_accuracy": 0.8296335831284523,
+      "num_tokens": 202141.0,
+      "step": 235
+    },
+    {
+      "epoch": 0.8173690932311622,
+      "grad_norm": 0.9807024002075195,
+      "learning_rate": 0.0001453924914675768,
+      "loss": 0.9295,
+      "mean_token_accuracy": 0.8495418474078178,
+      "num_tokens": 206333.0,
+      "step": 240
+    },
+    {
+      "epoch": 0.8343976160068114,
+      "grad_norm": 0.7864217162132263,
+      "learning_rate": 0.000144254835039818,
+      "loss": 1.0326,
+      "mean_token_accuracy": 0.8422158002853394,
+      "num_tokens": 210593.0,
+      "step": 245
+    },
+    {
+      "epoch": 0.8514261387824607,
+      "grad_norm": 0.8183476328849792,
+      "learning_rate": 0.00014311717861205915,
+      "loss": 1.0419,
+      "mean_token_accuracy": 0.8332764700055122,
+      "num_tokens": 214925.0,
+      "step": 250
+    },
+    {
+      "epoch": 0.8684546615581098,
+      "grad_norm": 0.7906543612480164,
+      "learning_rate": 0.00014197952218430036,
+      "loss": 0.9278,
+      "mean_token_accuracy": 0.8531344652175903,
+      "num_tokens": 219106.0,
+      "step": 255
+    },
+    {
+      "epoch": 0.885483184333759,
+      "grad_norm": 0.7864625453948975,
+      "learning_rate": 0.00014084186575654152,
+      "loss": 0.9764,
+      "mean_token_accuracy": 0.8394758701324463,
+      "num_tokens": 223398.0,
+      "step": 260
+    },
+    {
+      "epoch": 0.9025117071094083,
+      "grad_norm": 0.7231821417808533,
+      "learning_rate": 0.00013970420932878273,
+      "loss": 1.0357,
+      "mean_token_accuracy": 0.8368565306067467,
+      "num_tokens": 227720.0,
+      "step": 265
+    },
+    {
+      "epoch": 0.9195402298850575,
+      "grad_norm": 0.7288718223571777,
+      "learning_rate": 0.0001385665529010239,
+      "loss": 1.0178,
+      "mean_token_accuracy": 0.842984040081501,
+      "num_tokens": 232021.0,
+      "step": 270
+    },
+    {
+      "epoch": 0.9365687526607067,
+      "grad_norm": 0.7466130256652832,
+      "learning_rate": 0.0001374288964732651,
+      "loss": 0.9974,
+      "mean_token_accuracy": 0.8431279867887497,
+      "num_tokens": 236312.0,
+      "step": 275
+    },
+    {
+      "epoch": 0.9535972754363559,
+      "grad_norm": 0.7876543402671814,
+      "learning_rate": 0.00013629124004550626,
+      "loss": 1.0057,
+      "mean_token_accuracy": 0.8389794036746026,
+      "num_tokens": 240594.0,
+      "step": 280
+    },
+    {
+      "epoch": 0.9706257982120051,
+      "grad_norm": 0.738293468952179,
+      "learning_rate": 0.00013515358361774744,
+      "loss": 0.9129,
+      "mean_token_accuracy": 0.8528255730867386,
+      "num_tokens": 244859.0,
+      "step": 285
+    },
+    {
+      "epoch": 0.9876543209876543,
+      "grad_norm": 0.8145989775657654,
+      "learning_rate": 0.00013401592718998863,
+      "loss": 0.9188,
+      "mean_token_accuracy": 0.8555046319961548,
+      "num_tokens": 249060.0,
+      "step": 290
+    },
+    {
+      "epoch": 1.0046828437633035,
+      "grad_norm": 0.693233072757721,
+      "learning_rate": 0.00013287827076222981,
+      "loss": 1.0648,
+      "mean_token_accuracy": 0.8477524280548095,
+      "num_tokens": 253361.0,
+      "step": 295
+    },
+    {
+      "epoch": 1.0217113665389528,
+      "grad_norm": 0.8171095848083496,
+      "learning_rate": 0.000131740614334471,
+      "loss": 0.883,
+      "mean_token_accuracy": 0.8561580404639244,
+      "num_tokens": 257633.0,
+      "step": 300
+    },
+    {
+      "epoch": 1.038739889314602,
+      "grad_norm": 0.7343988418579102,
+      "learning_rate": 0.00013060295790671218,
+      "loss": 0.8591,
+      "mean_token_accuracy": 0.8583228841423989,
+      "num_tokens": 261975.0,
+      "step": 305
+    },
+    {
+      "epoch": 1.055768412090251,
+      "grad_norm": 0.6689726114273071,
+      "learning_rate": 0.00012946530147895337,
+      "loss": 0.8397,
+      "mean_token_accuracy": 0.8668102487921715,
+      "num_tokens": 266174.0,
+      "step": 310
+    },
+    {
+      "epoch": 1.0727969348659003,
+      "grad_norm": 0.8284767270088196,
+      "learning_rate": 0.00012832764505119455,
+      "loss": 0.9108,
+      "mean_token_accuracy": 0.8551412716507911,
+      "num_tokens": 270416.0,
+      "step": 315
+    },
+    {
+      "epoch": 1.0898254576415496,
+      "grad_norm": 0.7800877690315247,
+      "learning_rate": 0.0001271899886234357,
+      "loss": 0.923,
+      "mean_token_accuracy": 0.8521544948220253,
+      "num_tokens": 274802.0,
+      "step": 320
+    },
+    {
+      "epoch": 1.1068539804171988,
+      "grad_norm": 0.803035318851471,
+      "learning_rate": 0.00012605233219567692,
+      "loss": 0.9009,
+      "mean_token_accuracy": 0.8583568409085274,
+      "num_tokens": 279061.0,
+      "step": 325
+    },
+    {
+      "epoch": 1.123882503192848,
+      "grad_norm": 0.7928335666656494,
+      "learning_rate": 0.00012491467576791808,
+      "loss": 0.8677,
+      "mean_token_accuracy": 0.860838033258915,
+      "num_tokens": 283290.0,
+      "step": 330
+    },
+    {
+      "epoch": 1.1409110259684971,
+      "grad_norm": 0.82757967710495,
+      "learning_rate": 0.0001237770193401593,
+      "loss": 0.9326,
+      "mean_token_accuracy": 0.8526211172342301,
+      "num_tokens": 287627.0,
+      "step": 335
+    },
+    {
+      "epoch": 1.1579395487441464,
+      "grad_norm": 0.8021914958953857,
+      "learning_rate": 0.00012263936291240045,
+      "loss": 0.9066,
+      "mean_token_accuracy": 0.8505649596452713,
+      "num_tokens": 291975.0,
+      "step": 340
+    },
+    {
+      "epoch": 1.1749680715197957,
+      "grad_norm": 0.7565475106239319,
+      "learning_rate": 0.00012150170648464165,
+      "loss": 0.8812,
+      "mean_token_accuracy": 0.8562570214271545,
+      "num_tokens": 296232.0,
+      "step": 345
+    },
+    {
+      "epoch": 1.191996594295445,
+      "grad_norm": 0.8126978278160095,
+      "learning_rate": 0.00012036405005688282,
+      "loss": 0.905,
+      "mean_token_accuracy": 0.8556828230619431,
+      "num_tokens": 300591.0,
+      "step": 350
+    },
+    {
+      "epoch": 1.2090251170710942,
+      "grad_norm": 0.8174765706062317,
+      "learning_rate": 0.000119226393629124,
+      "loss": 0.9861,
+      "mean_token_accuracy": 0.8424012079834938,
+      "num_tokens": 304998.0,
+      "step": 355
+    },
+    {
+      "epoch": 1.2260536398467432,
+      "grad_norm": 0.8921035528182983,
+      "learning_rate": 0.00011808873720136519,
+      "loss": 0.7724,
+      "mean_token_accuracy": 0.8735315829515458,
+      "num_tokens": 309137.0,
+      "step": 360
+    },
+    {
+      "epoch": 1.2430821626223925,
+      "grad_norm": 0.855992317199707,
+      "learning_rate": 0.00011695108077360638,
+      "loss": 0.8922,
+      "mean_token_accuracy": 0.854039640724659,
+      "num_tokens": 313389.0,
+      "step": 365
+    },
+    {
+      "epoch": 1.2601106853980417,
+      "grad_norm": 0.9408860206604004,
+      "learning_rate": 0.00011581342434584756,
+      "loss": 0.9254,
+      "mean_token_accuracy": 0.8507854476571083,
+      "num_tokens": 317743.0,
+      "step": 370
+    },
+    {
+      "epoch": 1.277139208173691,
+      "grad_norm": 0.7847197651863098,
+      "learning_rate": 0.00011467576791808873,
+      "loss": 0.8563,
+      "mean_token_accuracy": 0.869862625002861,
+      "num_tokens": 321873.0,
+      "step": 375
+    },
+    {
+      "epoch": 1.29416773094934,
+      "grad_norm": 0.8556840419769287,
+      "learning_rate": 0.00011353811149032993,
+      "loss": 0.8489,
+      "mean_token_accuracy": 0.8591933220624923,
+      "num_tokens": 326124.0,
+      "step": 380
+    },
+    {
+      "epoch": 1.3111962537249893,
+      "grad_norm": 0.8849514126777649,
+      "learning_rate": 0.0001124004550625711,
+      "loss": 0.8526,
+      "mean_token_accuracy": 0.8600789621472359,
+      "num_tokens": 330405.0,
+      "step": 385
+    },
+    {
+      "epoch": 1.3282247765006385,
+      "grad_norm": 0.8099865913391113,
+      "learning_rate": 0.00011126279863481229,
+      "loss": 0.9309,
+      "mean_token_accuracy": 0.8511071890592575,
+      "num_tokens": 334701.0,
+      "step": 390
+    },
+    {
+      "epoch": 1.3452532992762878,
+      "grad_norm": 0.8668401837348938,
+      "learning_rate": 0.00011012514220705347,
+      "loss": 0.8671,
+      "mean_token_accuracy": 0.8605618432164193,
+      "num_tokens": 338951.0,
+      "step": 395
+    },
+    {
+      "epoch": 1.362281822051937,
+      "grad_norm": 0.8669872283935547,
+      "learning_rate": 0.00010898748577929466,
+      "loss": 0.8796,
+      "mean_token_accuracy": 0.8592276558279991,
+      "num_tokens": 343203.0,
+      "step": 400
+    }
+  ],
+  "logging_steps": 5,
+  "max_steps": 879,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 3,
+  "save_steps": 200,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 3216867264285696.0,
+  "train_batch_size": 1,
+  "trial_name": null,
+  "trial_params": null
+}

checkpoint-400/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:001de43419a04313fd3d652571d90911489fbcebf2f0e7c3f8aa624286dfc855
+size 5624

checkpoint-600/README.md

@@ -0,0 +1,209 @@
+---
+base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.20.0

checkpoint-600/adapter_config.json

@@ -0,0 +1,50 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "monteclora_config": null,
+  "peft_type": "LORA",
+  "peft_version": "0.20.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "up_proj",
+    "down_proj",
+    "k_proj",
+    "o_proj",
+    "v_proj",
+    "gate_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false,
+  "velora_config": null
+}

checkpoint-600/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9261875dab8ac5b2b5d3e1e5e603a884aec8cded38bbeabcea27b9a5b106e445
+size 73911112

checkpoint-600/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3f6730a6a08e8323e2f1997cc701d4bff7ff7099550655e1f07e63309c005255
+size 37969652

checkpoint-600/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cd31a88e8b6f456ee8b723e824bfcda938831d3f8391867e1379f24a6da62315
+size 14244

checkpoint-600/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7dd96493eebbb35a30ee240cfe1ad8f98b67771a20ddafde87bd6093f71d27bb
+size 1064

checkpoint-600/special_tokens_map.json

@@ -0,0 +1,17 @@
+{
+  "bos_token": {
+    "content": "<｜begin▁of▁sentence｜>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<｜end▁of▁sentence｜>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<｜end▁of▁sentence｜>"
+}

checkpoint-600/tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e20ddafc659ba90242154b55275402edeca0715e5dbb30f56815a4ce081f4893
+size 11422778

checkpoint-600/tokenizer_config.json

@@ -0,0 +1,194 @@
+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "add_prefix_space": null,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<｜end▁of▁sentence｜>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<｜User｜>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151645": {
+      "content": "<｜Assistant｜>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151646": {
+      "content": "<｜begin▁of▁sentence｜>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|EOT|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151648": {
+      "content": "<think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151649": {
+      "content": "</think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "bos_token": "<｜begin▁of▁sentence｜>",
+  "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<｜User｜>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<｜Assistant｜><｜tool▁calls▁begin｜><｜tool▁call▁begin��>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{%- set ns.is_first = true -%}{%- else %}{{'\\n' + '<｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{{'<｜tool▁calls▁end｜><｜end▁of▁sentence｜>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<｜tool▁outputs▁end｜>' + message['content'] + '<｜end▁of▁sentence｜>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<｜Assistant｜>' + content + '<｜end▁of▁sentence｜>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<｜tool▁outputs▁begin｜><｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\\n<｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<｜tool▁outputs▁end｜>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<｜Assistant｜><think>\\n'}}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<｜end▁of▁sentence｜>",
+  "legacy": true,
+  "model_max_length": 16384,
+  "pad_token": "<｜end▁of▁sentence｜>",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": null,
+  "use_default_system_prompt": false
+}

checkpoint-600/trainer_state.json

@@ -0,0 +1,1113 @@
+{
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 2.0434227330779056,
+  "eval_steps": 500,
+  "global_step": 600,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.017028522775649212,
+      "grad_norm": 2.3286359310150146,
+      "learning_rate": 0.0001988623435722412,
+      "loss": 4.1641,
+      "mean_token_accuracy": 0.3866006717085838,
+      "num_tokens": 4326.0,
+      "step": 5
+    },
+    {
+      "epoch": 0.034057045551298425,
+      "grad_norm": 1.4926602840423584,
+      "learning_rate": 0.00019772468714448238,
+      "loss": 2.0591,
+      "mean_token_accuracy": 0.6790341928601265,
+      "num_tokens": 8676.0,
+      "step": 10
+    },
+    {
+      "epoch": 0.05108556832694764,
+      "grad_norm": 1.0835968255996704,
+      "learning_rate": 0.00019658703071672356,
+      "loss": 1.3145,
+      "mean_token_accuracy": 0.8256841972470284,
+      "num_tokens": 12796.0,
+      "step": 15
+    },
+    {
+      "epoch": 0.06811409110259685,
+      "grad_norm": 0.7724414467811584,
+      "learning_rate": 0.00019544937428896475,
+      "loss": 1.3324,
+      "mean_token_accuracy": 0.8117582932114601,
+      "num_tokens": 17119.0,
+      "step": 20
+    },
+    {
+      "epoch": 0.08514261387824607,
+      "grad_norm": 0.785762369632721,
+      "learning_rate": 0.00019431171786120593,
+      "loss": 1.3375,
+      "mean_token_accuracy": 0.8029867172241211,
+      "num_tokens": 21499.0,
+      "step": 25
+    },
+    {
+      "epoch": 0.10217113665389528,
+      "grad_norm": 0.6702725291252136,
+      "learning_rate": 0.00019317406143344712,
+      "loss": 1.2159,
+      "mean_token_accuracy": 0.8230627462267875,
+      "num_tokens": 25785.0,
+      "step": 30
+    },
+    {
+      "epoch": 0.11919965942954448,
+      "grad_norm": 0.6287369728088379,
+      "learning_rate": 0.0001920364050056883,
+      "loss": 1.1634,
+      "mean_token_accuracy": 0.8315445825457572,
+      "num_tokens": 29980.0,
+      "step": 35
+    },
+    {
+      "epoch": 0.1362281822051937,
+      "grad_norm": 0.6573143005371094,
+      "learning_rate": 0.00019089874857792946,
+      "loss": 1.3762,
+      "mean_token_accuracy": 0.7971536681056023,
+      "num_tokens": 34497.0,
+      "step": 40
+    },
+    {
+      "epoch": 0.1532567049808429,
+      "grad_norm": 0.6560688614845276,
+      "learning_rate": 0.00018976109215017067,
+      "loss": 1.1589,
+      "mean_token_accuracy": 0.8251897826790809,
+      "num_tokens": 38800.0,
+      "step": 45
+    },
+    {
+      "epoch": 0.17028522775649213,
+      "grad_norm": 0.6654791831970215,
+      "learning_rate": 0.00018862343572241183,
+      "loss": 1.1498,
+      "mean_token_accuracy": 0.8319168403744698,
+      "num_tokens": 43055.0,
+      "step": 50
+    },
+    {
+      "epoch": 0.18731375053214133,
+      "grad_norm": 0.7387417554855347,
+      "learning_rate": 0.00018748577929465302,
+      "loss": 1.1265,
+      "mean_token_accuracy": 0.8290244281291962,
+      "num_tokens": 47346.0,
+      "step": 55
+    },
+    {
+      "epoch": 0.20434227330779056,
+      "grad_norm": 0.5795997977256775,
+      "learning_rate": 0.0001863481228668942,
+      "loss": 1.0046,
+      "mean_token_accuracy": 0.8534704640507698,
+      "num_tokens": 51485.0,
+      "step": 60
+    },
+    {
+      "epoch": 0.22137079608343976,
+      "grad_norm": 0.6834130883216858,
+      "learning_rate": 0.0001852104664391354,
+      "loss": 1.113,
+      "mean_token_accuracy": 0.8345914751291275,
+      "num_tokens": 55716.0,
+      "step": 65
+    },
+    {
+      "epoch": 0.23839931885908897,
+      "grad_norm": 0.7211284041404724,
+      "learning_rate": 0.00018407281001137657,
+      "loss": 1.2132,
+      "mean_token_accuracy": 0.8207321017980576,
+      "num_tokens": 60030.0,
+      "step": 70
+    },
+    {
+      "epoch": 0.2554278416347382,
+      "grad_norm": 0.6312271356582642,
+      "learning_rate": 0.00018293515358361776,
+      "loss": 1.0987,
+      "mean_token_accuracy": 0.8333725541830063,
+      "num_tokens": 64288.0,
+      "step": 75
+    },
+    {
+      "epoch": 0.2724563644103874,
+      "grad_norm": 0.7119404077529907,
+      "learning_rate": 0.00018179749715585894,
+      "loss": 1.0981,
+      "mean_token_accuracy": 0.8323698997497558,
+      "num_tokens": 68548.0,
+      "step": 80
+    },
+    {
+      "epoch": 0.2894848871860366,
+      "grad_norm": 0.9000201225280762,
+      "learning_rate": 0.00018065984072810013,
+      "loss": 1.146,
+      "mean_token_accuracy": 0.8253335595130921,
+      "num_tokens": 72914.0,
+      "step": 85
+    },
+    {
+      "epoch": 0.3065134099616858,
+      "grad_norm": 0.6050537824630737,
+      "learning_rate": 0.0001795221843003413,
+      "loss": 1.0111,
+      "mean_token_accuracy": 0.842674246430397,
+      "num_tokens": 77168.0,
+      "step": 90
+    },
+    {
+      "epoch": 0.32354193273733506,
+      "grad_norm": 0.684512197971344,
+      "learning_rate": 0.0001783845278725825,
+      "loss": 1.1186,
+      "mean_token_accuracy": 0.8351956441998482,
+      "num_tokens": 81439.0,
+      "step": 95
+    },
+    {
+      "epoch": 0.34057045551298426,
+      "grad_norm": 0.7323129773139954,
+      "learning_rate": 0.00017724687144482368,
+      "loss": 1.1287,
+      "mean_token_accuracy": 0.8245970487594605,
+      "num_tokens": 85773.0,
+      "step": 100
+    },
+    {
+      "epoch": 0.35759897828863346,
+      "grad_norm": 0.7547741532325745,
+      "learning_rate": 0.00017610921501706487,
+      "loss": 1.0868,
+      "mean_token_accuracy": 0.8298466548323631,
+      "num_tokens": 90117.0,
+      "step": 105
+    },
+    {
+      "epoch": 0.37462750106428266,
+      "grad_norm": 0.7113769054412842,
+      "learning_rate": 0.00017497155858930602,
+      "loss": 1.1214,
+      "mean_token_accuracy": 0.8299670115113258,
+      "num_tokens": 94412.0,
+      "step": 110
+    },
+    {
+      "epoch": 0.39165602383993187,
+      "grad_norm": 0.7486220002174377,
+      "learning_rate": 0.00017383390216154724,
+      "loss": 1.1452,
+      "mean_token_accuracy": 0.8283886179327965,
+      "num_tokens": 98782.0,
+      "step": 115
+    },
+    {
+      "epoch": 0.4086845466155811,
+      "grad_norm": 0.658633828163147,
+      "learning_rate": 0.0001726962457337884,
+      "loss": 1.0415,
+      "mean_token_accuracy": 0.8431179687380791,
+      "num_tokens": 103011.0,
+      "step": 120
+    },
+    {
+      "epoch": 0.4257130693912303,
+      "grad_norm": 0.783794105052948,
+      "learning_rate": 0.0001715585893060296,
+      "loss": 1.1056,
+      "mean_token_accuracy": 0.8254878520965576,
+      "num_tokens": 107402.0,
+      "step": 125
+    },
+    {
+      "epoch": 0.4427415921668795,
+      "grad_norm": 0.7954565286636353,
+      "learning_rate": 0.00017042093287827076,
+      "loss": 1.0518,
+      "mean_token_accuracy": 0.8375606715679169,
+      "num_tokens": 111707.0,
+      "step": 130
+    },
+    {
+      "epoch": 0.45977011494252873,
+      "grad_norm": 0.6913949847221375,
+      "learning_rate": 0.00016928327645051198,
+      "loss": 1.1104,
+      "mean_token_accuracy": 0.8326424166560173,
+      "num_tokens": 115998.0,
+      "step": 135
+    },
+    {
+      "epoch": 0.47679863771817793,
+      "grad_norm": 0.7918037176132202,
+      "learning_rate": 0.00016814562002275313,
+      "loss": 1.0495,
+      "mean_token_accuracy": 0.8390962019562721,
+      "num_tokens": 120271.0,
+      "step": 140
+    },
+    {
+      "epoch": 0.49382716049382713,
+      "grad_norm": 0.7816826701164246,
+      "learning_rate": 0.00016700796359499432,
+      "loss": 1.0463,
+      "mean_token_accuracy": 0.8433194428682327,
+      "num_tokens": 124461.0,
+      "step": 145
+    },
+    {
+      "epoch": 0.5108556832694764,
+      "grad_norm": 0.8069042563438416,
+      "learning_rate": 0.0001658703071672355,
+      "loss": 1.0664,
+      "mean_token_accuracy": 0.8278923153877258,
+      "num_tokens": 128781.0,
+      "step": 150
+    },
+    {
+      "epoch": 0.5278842060451255,
+      "grad_norm": 1.0114731788635254,
+      "learning_rate": 0.0001647326507394767,
+      "loss": 1.1217,
+      "mean_token_accuracy": 0.8267972275614739,
+      "num_tokens": 133167.0,
+      "step": 155
+    },
+    {
+      "epoch": 0.5449127288207748,
+      "grad_norm": 0.7900378704071045,
+      "learning_rate": 0.00016359499431171787,
+      "loss": 0.971,
+      "mean_token_accuracy": 0.8421565622091294,
+      "num_tokens": 137464.0,
+      "step": 160
+    },
+    {
+      "epoch": 0.561941251596424,
+      "grad_norm": 0.8059927821159363,
+      "learning_rate": 0.00016245733788395906,
+      "loss": 1.0457,
+      "mean_token_accuracy": 0.8381335601210594,
+      "num_tokens": 141760.0,
+      "step": 165
+    },
+    {
+      "epoch": 0.5789697743720732,
+      "grad_norm": 0.7589371800422668,
+      "learning_rate": 0.00016131968145620024,
+      "loss": 1.0208,
+      "mean_token_accuracy": 0.8342296928167343,
+      "num_tokens": 146051.0,
+      "step": 170
+    },
+    {
+      "epoch": 0.5959982971477225,
+      "grad_norm": 0.692416250705719,
+      "learning_rate": 0.00016018202502844143,
+      "loss": 0.9837,
+      "mean_token_accuracy": 0.8510025009512902,
+      "num_tokens": 150270.0,
+      "step": 175
+    },
+    {
+      "epoch": 0.6130268199233716,
+      "grad_norm": 0.6662923097610474,
+      "learning_rate": 0.0001590443686006826,
+      "loss": 0.9835,
+      "mean_token_accuracy": 0.8463438332080842,
+      "num_tokens": 154537.0,
+      "step": 180
+    },
+    {
+      "epoch": 0.6300553426990209,
+      "grad_norm": 0.7452691793441772,
+      "learning_rate": 0.0001579067121729238,
+      "loss": 1.0496,
+      "mean_token_accuracy": 0.8375737622380257,
+      "num_tokens": 158810.0,
+      "step": 185
+    },
+    {
+      "epoch": 0.6470838654746701,
+      "grad_norm": 0.809700608253479,
+      "learning_rate": 0.00015676905574516496,
+      "loss": 1.0595,
+      "mean_token_accuracy": 0.8294038504362107,
+      "num_tokens": 163213.0,
+      "step": 190
+    },
+    {
+      "epoch": 0.6641123882503193,
+      "grad_norm": 0.7708745002746582,
+      "learning_rate": 0.00015563139931740617,
+      "loss": 1.0976,
+      "mean_token_accuracy": 0.8289313957095146,
+      "num_tokens": 167607.0,
+      "step": 195
+    },
+    {
+      "epoch": 0.6811409110259685,
+      "grad_norm": 0.6482141613960266,
+      "learning_rate": 0.00015449374288964733,
+      "loss": 1.0701,
+      "mean_token_accuracy": 0.8261386752128601,
+      "num_tokens": 172024.0,
+      "step": 200
+    },
+    {
+      "epoch": 0.6981694338016177,
+      "grad_norm": 0.7164883613586426,
+      "learning_rate": 0.00015335608646188854,
+      "loss": 0.9878,
+      "mean_token_accuracy": 0.8418964132666588,
+      "num_tokens": 176317.0,
+      "step": 205
+    },
+    {
+      "epoch": 0.7151979565772669,
+      "grad_norm": 0.710343599319458,
+      "learning_rate": 0.0001522184300341297,
+      "loss": 0.9306,
+      "mean_token_accuracy": 0.8468034327030182,
+      "num_tokens": 180558.0,
+      "step": 210
+    },
+    {
+      "epoch": 0.7322264793529162,
+      "grad_norm": 0.863784909248352,
+      "learning_rate": 0.00015108077360637088,
+      "loss": 1.0544,
+      "mean_token_accuracy": 0.8359945684671402,
+      "num_tokens": 184885.0,
+      "step": 215
+    },
+    {
+      "epoch": 0.7492550021285653,
+      "grad_norm": 0.8381637930870056,
+      "learning_rate": 0.00014994311717861207,
+      "loss": 1.0522,
+      "mean_token_accuracy": 0.836811026930809,
+      "num_tokens": 189219.0,
+      "step": 220
+    },
+    {
+      "epoch": 0.7662835249042146,
+      "grad_norm": 0.683501124382019,
+      "learning_rate": 0.00014880546075085325,
+      "loss": 0.9427,
+      "mean_token_accuracy": 0.8544979348778725,
+      "num_tokens": 193437.0,
+      "step": 225
+    },
+    {
+      "epoch": 0.7833120476798637,
+      "grad_norm": 0.7609812617301941,
+      "learning_rate": 0.00014766780432309444,
+      "loss": 1.0048,
+      "mean_token_accuracy": 0.8403829500079155,
+      "num_tokens": 197724.0,
+      "step": 230
+    },
+    {
+      "epoch": 0.800340570455513,
+      "grad_norm": 0.8223949074745178,
+      "learning_rate": 0.00014653014789533562,
+      "loss": 1.078,
+      "mean_token_accuracy": 0.8296335831284523,
+      "num_tokens": 202141.0,
+      "step": 235
+    },
+    {
+      "epoch": 0.8173690932311622,
+      "grad_norm": 0.9807024002075195,
+      "learning_rate": 0.0001453924914675768,
+      "loss": 0.9295,
+      "mean_token_accuracy": 0.8495418474078178,
+      "num_tokens": 206333.0,
+      "step": 240
+    },
+    {
+      "epoch": 0.8343976160068114,
+      "grad_norm": 0.7864217162132263,
+      "learning_rate": 0.000144254835039818,
+      "loss": 1.0326,
+      "mean_token_accuracy": 0.8422158002853394,
+      "num_tokens": 210593.0,
+      "step": 245
+    },
+    {
+      "epoch": 0.8514261387824607,
+      "grad_norm": 0.8183476328849792,
+      "learning_rate": 0.00014311717861205915,
+      "loss": 1.0419,
+      "mean_token_accuracy": 0.8332764700055122,
+      "num_tokens": 214925.0,
+      "step": 250
+    },
+    {
+      "epoch": 0.8684546615581098,
+      "grad_norm": 0.7906543612480164,
+      "learning_rate": 0.00014197952218430036,
+      "loss": 0.9278,
+      "mean_token_accuracy": 0.8531344652175903,
+      "num_tokens": 219106.0,
+      "step": 255
+    },
+    {
+      "epoch": 0.885483184333759,
+      "grad_norm": 0.7864625453948975,
+      "learning_rate": 0.00014084186575654152,
+      "loss": 0.9764,
+      "mean_token_accuracy": 0.8394758701324463,
+      "num_tokens": 223398.0,
+      "step": 260
+    },
+    {
+      "epoch": 0.9025117071094083,
+      "grad_norm": 0.7231821417808533,
+      "learning_rate": 0.00013970420932878273,
+      "loss": 1.0357,
+      "mean_token_accuracy": 0.8368565306067467,
+      "num_tokens": 227720.0,
+      "step": 265
+    },
+    {
+      "epoch": 0.9195402298850575,
+      "grad_norm": 0.7288718223571777,
+      "learning_rate": 0.0001385665529010239,
+      "loss": 1.0178,
+      "mean_token_accuracy": 0.842984040081501,
+      "num_tokens": 232021.0,
+      "step": 270
+    },
+    {
+      "epoch": 0.9365687526607067,
+      "grad_norm": 0.7466130256652832,
+      "learning_rate": 0.0001374288964732651,
+      "loss": 0.9974,
+      "mean_token_accuracy": 0.8431279867887497,
+      "num_tokens": 236312.0,
+      "step": 275
+    },
+    {
+      "epoch": 0.9535972754363559,
+      "grad_norm": 0.7876543402671814,
+      "learning_rate": 0.00013629124004550626,
+      "loss": 1.0057,
+      "mean_token_accuracy": 0.8389794036746026,
+      "num_tokens": 240594.0,
+      "step": 280
+    },
+    {
+      "epoch": 0.9706257982120051,
+      "grad_norm": 0.738293468952179,
+      "learning_rate": 0.00013515358361774744,
+      "loss": 0.9129,
+      "mean_token_accuracy": 0.8528255730867386,
+      "num_tokens": 244859.0,
+      "step": 285
+    },
+    {
+      "epoch": 0.9876543209876543,
+      "grad_norm": 0.8145989775657654,
+      "learning_rate": 0.00013401592718998863,
+      "loss": 0.9188,
+      "mean_token_accuracy": 0.8555046319961548,
+      "num_tokens": 249060.0,
+      "step": 290
+    },
+    {
+      "epoch": 1.0046828437633035,
+      "grad_norm": 0.693233072757721,
+      "learning_rate": 0.00013287827076222981,
+      "loss": 1.0648,
+      "mean_token_accuracy": 0.8477524280548095,
+      "num_tokens": 253361.0,
+      "step": 295
+    },
+    {
+      "epoch": 1.0217113665389528,
+      "grad_norm": 0.8171095848083496,
+      "learning_rate": 0.000131740614334471,
+      "loss": 0.883,
+      "mean_token_accuracy": 0.8561580404639244,
+      "num_tokens": 257633.0,
+      "step": 300
+    },
+    {
+      "epoch": 1.038739889314602,
+      "grad_norm": 0.7343988418579102,
+      "learning_rate": 0.00013060295790671218,
+      "loss": 0.8591,
+      "mean_token_accuracy": 0.8583228841423989,
+      "num_tokens": 261975.0,
+      "step": 305
+    },
+    {
+      "epoch": 1.055768412090251,
+      "grad_norm": 0.6689726114273071,
+      "learning_rate": 0.00012946530147895337,
+      "loss": 0.8397,
+      "mean_token_accuracy": 0.8668102487921715,
+      "num_tokens": 266174.0,
+      "step": 310
+    },
+    {
+      "epoch": 1.0727969348659003,
+      "grad_norm": 0.8284767270088196,
+      "learning_rate": 0.00012832764505119455,
+      "loss": 0.9108,
+      "mean_token_accuracy": 0.8551412716507911,
+      "num_tokens": 270416.0,
+      "step": 315
+    },
+    {
+      "epoch": 1.0898254576415496,
+      "grad_norm": 0.7800877690315247,
+      "learning_rate": 0.0001271899886234357,
+      "loss": 0.923,
+      "mean_token_accuracy": 0.8521544948220253,
+      "num_tokens": 274802.0,
+      "step": 320
+    },
+    {
+      "epoch": 1.1068539804171988,
+      "grad_norm": 0.803035318851471,
+      "learning_rate": 0.00012605233219567692,
+      "loss": 0.9009,
+      "mean_token_accuracy": 0.8583568409085274,
+      "num_tokens": 279061.0,
+      "step": 325
+    },
+    {
+      "epoch": 1.123882503192848,
+      "grad_norm": 0.7928335666656494,
+      "learning_rate": 0.00012491467576791808,
+      "loss": 0.8677,
+      "mean_token_accuracy": 0.860838033258915,
+      "num_tokens": 283290.0,
+      "step": 330
+    },
+    {
+      "epoch": 1.1409110259684971,
+      "grad_norm": 0.82757967710495,
+      "learning_rate": 0.0001237770193401593,
+      "loss": 0.9326,
+      "mean_token_accuracy": 0.8526211172342301,
+      "num_tokens": 287627.0,
+      "step": 335
+    },
+    {
+      "epoch": 1.1579395487441464,
+      "grad_norm": 0.8021914958953857,
+      "learning_rate": 0.00012263936291240045,
+      "loss": 0.9066,
+      "mean_token_accuracy": 0.8505649596452713,
+      "num_tokens": 291975.0,
+      "step": 340
+    },
+    {
+      "epoch": 1.1749680715197957,
+      "grad_norm": 0.7565475106239319,
+      "learning_rate": 0.00012150170648464165,
+      "loss": 0.8812,
+      "mean_token_accuracy": 0.8562570214271545,
+      "num_tokens": 296232.0,
+      "step": 345
+    },
+    {
+      "epoch": 1.191996594295445,
+      "grad_norm": 0.8126978278160095,
+      "learning_rate": 0.00012036405005688282,
+      "loss": 0.905,
+      "mean_token_accuracy": 0.8556828230619431,
+      "num_tokens": 300591.0,
+      "step": 350
+    },
+    {
+      "epoch": 1.2090251170710942,
+      "grad_norm": 0.8174765706062317,
+      "learning_rate": 0.000119226393629124,
+      "loss": 0.9861,
+      "mean_token_accuracy": 0.8424012079834938,
+      "num_tokens": 304998.0,
+      "step": 355
+    },
+    {
+      "epoch": 1.2260536398467432,
+      "grad_norm": 0.8921035528182983,
+      "learning_rate": 0.00011808873720136519,
+      "loss": 0.7724,
+      "mean_token_accuracy": 0.8735315829515458,
+      "num_tokens": 309137.0,
+      "step": 360
+    },
+    {
+      "epoch": 1.2430821626223925,
+      "grad_norm": 0.855992317199707,
+      "learning_rate": 0.00011695108077360638,
+      "loss": 0.8922,
+      "mean_token_accuracy": 0.854039640724659,
+      "num_tokens": 313389.0,
+      "step": 365
+    },
+    {
+      "epoch": 1.2601106853980417,
+      "grad_norm": 0.9408860206604004,
+      "learning_rate": 0.00011581342434584756,
+      "loss": 0.9254,
+      "mean_token_accuracy": 0.8507854476571083,
+      "num_tokens": 317743.0,
+      "step": 370
+    },
+    {
+      "epoch": 1.277139208173691,
+      "grad_norm": 0.7847197651863098,
+      "learning_rate": 0.00011467576791808873,
+      "loss": 0.8563,
+      "mean_token_accuracy": 0.869862625002861,
+      "num_tokens": 321873.0,
+      "step": 375
+    },
+    {
+      "epoch": 1.29416773094934,
+      "grad_norm": 0.8556840419769287,
+      "learning_rate": 0.00011353811149032993,
+      "loss": 0.8489,
+      "mean_token_accuracy": 0.8591933220624923,
+      "num_tokens": 326124.0,
+      "step": 380
+    },
+    {
+      "epoch": 1.3111962537249893,
+      "grad_norm": 0.8849514126777649,
+      "learning_rate": 0.0001124004550625711,
+      "loss": 0.8526,
+      "mean_token_accuracy": 0.8600789621472359,
+      "num_tokens": 330405.0,
+      "step": 385
+    },
+    {
+      "epoch": 1.3282247765006385,
+      "grad_norm": 0.8099865913391113,
+      "learning_rate": 0.00011126279863481229,
+      "loss": 0.9309,
+      "mean_token_accuracy": 0.8511071890592575,
+      "num_tokens": 334701.0,
+      "step": 390
+    },
+    {
+      "epoch": 1.3452532992762878,
+      "grad_norm": 0.8668401837348938,
+      "learning_rate": 0.00011012514220705347,
+      "loss": 0.8671,
+      "mean_token_accuracy": 0.8605618432164193,
+      "num_tokens": 338951.0,
+      "step": 395
+    },
+    {
+      "epoch": 1.362281822051937,
+      "grad_norm": 0.8669872283935547,
+      "learning_rate": 0.00010898748577929466,
+      "loss": 0.8796,
+      "mean_token_accuracy": 0.8592276558279991,
+      "num_tokens": 343203.0,
+      "step": 400
+    },
+    {
+      "epoch": 1.3793103448275863,
+      "grad_norm": 0.8468757271766663,
+      "learning_rate": 0.00010784982935153584,
+      "loss": 0.8941,
+      "mean_token_accuracy": 0.8553030788898468,
+      "num_tokens": 347460.0,
+      "step": 405
+    },
+    {
+      "epoch": 1.3963388676032356,
+      "grad_norm": 0.8839651346206665,
+      "learning_rate": 0.00010671217292377703,
+      "loss": 0.913,
+      "mean_token_accuracy": 0.8489826336503029,
+      "num_tokens": 351850.0,
+      "step": 410
+    },
+    {
+      "epoch": 1.4133673903788846,
+      "grad_norm": 0.8808367848396301,
+      "learning_rate": 0.00010557451649601821,
+      "loss": 0.8158,
+      "mean_token_accuracy": 0.8628147393465042,
+      "num_tokens": 356104.0,
+      "step": 415
+    },
+    {
+      "epoch": 1.4303959131545338,
+      "grad_norm": 0.9303593039512634,
+      "learning_rate": 0.00010443686006825938,
+      "loss": 0.8737,
+      "mean_token_accuracy": 0.8497098922729492,
+      "num_tokens": 360445.0,
+      "step": 420
+    },
+    {
+      "epoch": 1.447424435930183,
+      "grad_norm": 0.7914776802062988,
+      "learning_rate": 0.00010329920364050057,
+      "loss": 0.9168,
+      "mean_token_accuracy": 0.8531492814421654,
+      "num_tokens": 364778.0,
+      "step": 425
+    },
+    {
+      "epoch": 1.4644529587058321,
+      "grad_norm": 0.8661580085754395,
+      "learning_rate": 0.00010216154721274175,
+      "loss": 0.8335,
+      "mean_token_accuracy": 0.8674297228455543,
+      "num_tokens": 368961.0,
+      "step": 430
+    },
+    {
+      "epoch": 1.4814814814814814,
+      "grad_norm": 0.8548939228057861,
+      "learning_rate": 0.00010102389078498294,
+      "loss": 0.9314,
+      "mean_token_accuracy": 0.8409372463822364,
+      "num_tokens": 373355.0,
+      "step": 435
+    },
+    {
+      "epoch": 1.4985100042571307,
+      "grad_norm": 0.8668932914733887,
+      "learning_rate": 9.988623435722412e-05,
+      "loss": 0.8482,
+      "mean_token_accuracy": 0.8576690852642059,
+      "num_tokens": 377652.0,
+      "step": 440
+    },
+    {
+      "epoch": 1.51553852703278,
+      "grad_norm": 0.8412478566169739,
+      "learning_rate": 9.874857792946531e-05,
+      "loss": 0.8791,
+      "mean_token_accuracy": 0.8531419888138772,
+      "num_tokens": 381969.0,
+      "step": 445
+    },
+    {
+      "epoch": 1.5325670498084292,
+      "grad_norm": 0.8298078179359436,
+      "learning_rate": 9.761092150170649e-05,
+      "loss": 0.7418,
+      "mean_token_accuracy": 0.8757623940706253,
+      "num_tokens": 386149.0,
+      "step": 450
+    },
+    {
+      "epoch": 1.5495955725840784,
+      "grad_norm": 0.8505256772041321,
+      "learning_rate": 9.647326507394768e-05,
+      "loss": 0.8107,
+      "mean_token_accuracy": 0.8660028412938118,
+      "num_tokens": 390316.0,
+      "step": 455
+    },
+    {
+      "epoch": 1.5666240953597277,
+      "grad_norm": 0.72185879945755,
+      "learning_rate": 9.533560864618886e-05,
+      "loss": 0.8601,
+      "mean_token_accuracy": 0.8591737478971482,
+      "num_tokens": 394651.0,
+      "step": 460
+    },
+    {
+      "epoch": 1.5836526181353767,
+      "grad_norm": 1.0382378101348877,
+      "learning_rate": 9.419795221843003e-05,
+      "loss": 0.849,
+      "mean_token_accuracy": 0.8591210901737213,
+      "num_tokens": 398879.0,
+      "step": 465
+    },
+    {
+      "epoch": 1.600681140911026,
+      "grad_norm": 0.7781236171722412,
+      "learning_rate": 9.306029579067122e-05,
+      "loss": 0.8587,
+      "mean_token_accuracy": 0.8554968953132629,
+      "num_tokens": 403154.0,
+      "step": 470
+    },
+    {
+      "epoch": 1.617709663686675,
+      "grad_norm": 0.9941114187240601,
+      "learning_rate": 9.19226393629124e-05,
+      "loss": 1.0077,
+      "mean_token_accuracy": 0.8324473947286606,
+      "num_tokens": 407653.0,
+      "step": 475
+    },
+    {
+      "epoch": 1.6347381864623243,
+      "grad_norm": 0.791912853717804,
+      "learning_rate": 9.078498293515359e-05,
+      "loss": 0.8211,
+      "mean_token_accuracy": 0.8655396267771721,
+      "num_tokens": 411904.0,
+      "step": 480
+    },
+    {
+      "epoch": 1.6517667092379735,
+      "grad_norm": 0.8509976267814636,
+      "learning_rate": 8.964732650739477e-05,
+      "loss": 0.8895,
+      "mean_token_accuracy": 0.8587504833936691,
+      "num_tokens": 416159.0,
+      "step": 485
+    },
+    {
+      "epoch": 1.6687952320136228,
+      "grad_norm": 1.0071176290512085,
+      "learning_rate": 8.850967007963596e-05,
+      "loss": 0.9112,
+      "mean_token_accuracy": 0.8539686873555183,
+      "num_tokens": 420513.0,
+      "step": 490
+    },
+    {
+      "epoch": 1.685823754789272,
+      "grad_norm": 0.8273159861564636,
+      "learning_rate": 8.737201365187714e-05,
+      "loss": 0.8383,
+      "mean_token_accuracy": 0.8577379778027534,
+      "num_tokens": 424759.0,
+      "step": 495
+    },
+    {
+      "epoch": 1.7028522775649213,
+      "grad_norm": 0.8064838647842407,
+      "learning_rate": 8.623435722411833e-05,
+      "loss": 0.8397,
+      "mean_token_accuracy": 0.8636475175619125,
+      "num_tokens": 429018.0,
+      "step": 500
+    },
+    {
+      "epoch": 1.7198808003405706,
+      "grad_norm": 0.7176003456115723,
+      "learning_rate": 8.509670079635951e-05,
+      "loss": 0.7738,
+      "mean_token_accuracy": 0.8699946105480194,
+      "num_tokens": 433124.0,
+      "step": 505
+    },
+    {
+      "epoch": 1.7369093231162198,
+      "grad_norm": 0.8316643834114075,
+      "learning_rate": 8.395904436860069e-05,
+      "loss": 0.9191,
+      "mean_token_accuracy": 0.8493718564510345,
+      "num_tokens": 437449.0,
+      "step": 510
+    },
+    {
+      "epoch": 1.7539378458918689,
+      "grad_norm": 0.9423941373825073,
+      "learning_rate": 8.282138794084187e-05,
+      "loss": 0.8749,
+      "mean_token_accuracy": 0.8558909714221954,
+      "num_tokens": 441753.0,
+      "step": 515
+    },
+    {
+      "epoch": 1.770966368667518,
+      "grad_norm": 0.8593487739562988,
+      "learning_rate": 8.168373151308306e-05,
+      "loss": 0.8463,
+      "mean_token_accuracy": 0.857591399550438,
+      "num_tokens": 446036.0,
+      "step": 520
+    },
+    {
+      "epoch": 1.7879948914431671,
+      "grad_norm": 0.7944974303245544,
+      "learning_rate": 8.054607508532424e-05,
+      "loss": 0.8275,
+      "mean_token_accuracy": 0.859096622467041,
+      "num_tokens": 450298.0,
+      "step": 525
+    },
+    {
+      "epoch": 1.8050234142188164,
+      "grad_norm": 0.7622503042221069,
+      "learning_rate": 7.940841865756543e-05,
+      "loss": 0.8846,
+      "mean_token_accuracy": 0.8580268025398254,
+      "num_tokens": 454595.0,
+      "step": 530
+    },
+    {
+      "epoch": 1.8220519369944657,
+      "grad_norm": 0.8578078746795654,
+      "learning_rate": 7.827076222980661e-05,
+      "loss": 0.7674,
+      "mean_token_accuracy": 0.8716912001371384,
+      "num_tokens": 458807.0,
+      "step": 535
+    },
+    {
+      "epoch": 1.839080459770115,
+      "grad_norm": 1.0383292436599731,
+      "learning_rate": 7.71331058020478e-05,
+      "loss": 0.9129,
+      "mean_token_accuracy": 0.8489386543631554,
+      "num_tokens": 463150.0,
+      "step": 540
+    },
+    {
+      "epoch": 1.8561089825457642,
+      "grad_norm": 0.8726801872253418,
+      "learning_rate": 7.599544937428897e-05,
+      "loss": 0.877,
+      "mean_token_accuracy": 0.8568779289722442,
+      "num_tokens": 467472.0,
+      "step": 545
+    },
+    {
+      "epoch": 1.8731375053214134,
+      "grad_norm": 0.9192221164703369,
+      "learning_rate": 7.485779294653015e-05,
+      "loss": 0.9341,
+      "mean_token_accuracy": 0.8403045237064362,
+      "num_tokens": 471930.0,
+      "step": 550
+    },
+    {
+      "epoch": 1.8901660280970627,
+      "grad_norm": 0.8688830137252808,
+      "learning_rate": 7.372013651877134e-05,
+      "loss": 0.8244,
+      "mean_token_accuracy": 0.8679932355880737,
+      "num_tokens": 476140.0,
+      "step": 555
+    },
+    {
+      "epoch": 1.907194550872712,
+      "grad_norm": 0.8286635279655457,
+      "learning_rate": 7.258248009101252e-05,
+      "loss": 0.8725,
+      "mean_token_accuracy": 0.8549414992332458,
+      "num_tokens": 480474.0,
+      "step": 560
+    },
+    {
+      "epoch": 1.924223073648361,
+      "grad_norm": 0.789902925491333,
+      "learning_rate": 7.14448236632537e-05,
+      "loss": 0.8135,
+      "mean_token_accuracy": 0.8649365425109863,
+      "num_tokens": 484805.0,
+      "step": 565
+    },
+    {
+      "epoch": 1.9412515964240102,
+      "grad_norm": 0.8496629595756531,
+      "learning_rate": 7.030716723549489e-05,
+      "loss": 0.9036,
+      "mean_token_accuracy": 0.8460123494267464,
+      "num_tokens": 489275.0,
+      "step": 570
+    },
+    {
+      "epoch": 1.9582801191996593,
+      "grad_norm": 0.8411655426025391,
+      "learning_rate": 6.916951080773608e-05,
+      "loss": 0.9346,
+      "mean_token_accuracy": 0.8429780200123786,
+      "num_tokens": 493726.0,
+      "step": 575
+    },
+    {
+      "epoch": 1.9753086419753085,
+      "grad_norm": 0.8502522706985474,
+      "learning_rate": 6.803185437997726e-05,
+      "loss": 0.8703,
+      "mean_token_accuracy": 0.8595944106578827,
+      "num_tokens": 498022.0,
+      "step": 580
+    },
+    {
+      "epoch": 1.9923371647509578,
+      "grad_norm": 0.743918776512146,
+      "learning_rate": 6.689419795221843e-05,
+      "loss": 0.8815,
+      "mean_token_accuracy": 0.851164074242115,
+      "num_tokens": 502352.0,
+      "step": 585
+    },
+    {
+      "epoch": 2.009365687526607,
+      "grad_norm": 0.7339876294136047,
+      "learning_rate": 6.575654152445962e-05,
+      "loss": 0.9297,
+      "mean_token_accuracy": 0.8610147342085839,
+      "num_tokens": 506669.0,
+      "step": 590
+    },
+    {
+      "epoch": 2.0263942103022563,
+      "grad_norm": 0.903137743473053,
+      "learning_rate": 6.46188850967008e-05,
+      "loss": 0.7306,
+      "mean_token_accuracy": 0.8799364000558854,
+      "num_tokens": 510931.0,
+      "step": 595
+    },
+    {
+      "epoch": 2.0434227330779056,
+      "grad_norm": 0.8741887807846069,
+      "learning_rate": 6.348122866894199e-05,
+      "loss": 0.777,
+      "mean_token_accuracy": 0.8718036338686943,
+      "num_tokens": 515254.0,
+      "step": 600
+    }
+  ],
+  "logging_steps": 5,
+  "max_steps": 879,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 3,
+  "save_steps": 200,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 4829514093385728.0,
+  "train_batch_size": 1,
+  "trial_name": null,
+  "trial_params": null
+}

checkpoint-600/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:001de43419a04313fd3d652571d90911489fbcebf2f0e7c3f8aa624286dfc855
+size 5624

checkpoint-800/README.md

@@ -0,0 +1,209 @@
+---
+base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.20.0

checkpoint-800/adapter_config.json

@@ -0,0 +1,50 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "monteclora_config": null,
+  "peft_type": "LORA",
+  "peft_version": "0.20.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "up_proj",
+    "down_proj",
+    "k_proj",
+    "o_proj",
+    "v_proj",
+    "gate_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false,
+  "velora_config": null
+}

checkpoint-800/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ea24aeceaec80fb0138939f3558532bc2db231c414389386eb51ff8189f36259
+size 73911112

checkpoint-800/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f5c6ab7e0d89ede34156f55c028f335e3537021f90a5e2c16e68c96b6c45f443
+size 37969652

checkpoint-800/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:576b248a6f84ac7055634ab569d402f9bf88c78821a9ad088c8950d62e42907a
+size 14244

checkpoint-800/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4225c4e9f1ab7f7ed353e670836f9ef1773c433469b40387b8cbe0244cf93748
+size 1064

checkpoint-800/special_tokens_map.json

@@ -0,0 +1,17 @@
+{
+  "bos_token": {
+    "content": "<｜begin▁of▁sentence｜>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<｜end▁of▁sentence｜>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<｜end▁of▁sentence｜>"
+}

checkpoint-800/tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e20ddafc659ba90242154b55275402edeca0715e5dbb30f56815a4ce081f4893
+size 11422778

checkpoint-800/tokenizer_config.json

@@ -0,0 +1,194 @@
+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "add_prefix_space": null,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<｜end▁of▁sentence｜>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<｜User｜>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151645": {
+      "content": "<｜Assistant｜>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151646": {
+      "content": "<｜begin▁of▁sentence｜>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|EOT|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151648": {
+      "content": "<think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151649": {
+      "content": "</think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "bos_token": "<｜begin▁of▁sentence｜>",
+  "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<｜User｜>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<｜Assistant｜><｜tool▁calls▁begin｜><｜tool▁call▁begin��>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{%- set ns.is_first = true -%}{%- else %}{{'\\n' + '<｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{{'<｜tool▁calls▁end｜><｜end▁of▁sentence｜>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<｜tool▁outputs▁end｜>' + message['content'] + '<｜end▁of▁sentence｜>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<｜Assistant｜>' + content + '<｜end▁of▁sentence｜>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<｜tool▁outputs▁begin｜><｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\\n<｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<｜tool▁outputs▁end｜>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<｜Assistant｜><think>\\n'}}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<｜end▁of▁sentence｜>",
+  "legacy": true,
+  "model_max_length": 16384,
+  "pad_token": "<｜end▁of▁sentence｜>",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": null,
+  "use_default_system_prompt": false
+}

checkpoint-800/trainer_state.json

@@ -0,0 +1,1473 @@
+{
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 2.724563644103874,
+  "eval_steps": 500,
+  "global_step": 800,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.017028522775649212,
+      "grad_norm": 2.3286359310150146,
+      "learning_rate": 0.0001988623435722412,
+      "loss": 4.1641,
+      "mean_token_accuracy": 0.3866006717085838,
+      "num_tokens": 4326.0,
+      "step": 5
+    },
+    {
+      "epoch": 0.034057045551298425,
+      "grad_norm": 1.4926602840423584,
+      "learning_rate": 0.00019772468714448238,
+      "loss": 2.0591,
+      "mean_token_accuracy": 0.6790341928601265,
+      "num_tokens": 8676.0,
+      "step": 10
+    },
+    {
+      "epoch": 0.05108556832694764,
+      "grad_norm": 1.0835968255996704,
+      "learning_rate": 0.00019658703071672356,
+      "loss": 1.3145,
+      "mean_token_accuracy": 0.8256841972470284,
+      "num_tokens": 12796.0,
+      "step": 15
+    },
+    {
+      "epoch": 0.06811409110259685,
+      "grad_norm": 0.7724414467811584,
+      "learning_rate": 0.00019544937428896475,
+      "loss": 1.3324,
+      "mean_token_accuracy": 0.8117582932114601,
+      "num_tokens": 17119.0,
+      "step": 20
+    },
+    {
+      "epoch": 0.08514261387824607,
+      "grad_norm": 0.785762369632721,
+      "learning_rate": 0.00019431171786120593,
+      "loss": 1.3375,
+      "mean_token_accuracy": 0.8029867172241211,
+      "num_tokens": 21499.0,
+      "step": 25
+    },
+    {
+      "epoch": 0.10217113665389528,
+      "grad_norm": 0.6702725291252136,
+      "learning_rate": 0.00019317406143344712,
+      "loss": 1.2159,
+      "mean_token_accuracy": 0.8230627462267875,
+      "num_tokens": 25785.0,
+      "step": 30
+    },
+    {
+      "epoch": 0.11919965942954448,
+      "grad_norm": 0.6287369728088379,
+      "learning_rate": 0.0001920364050056883,
+      "loss": 1.1634,
+      "mean_token_accuracy": 0.8315445825457572,
+      "num_tokens": 29980.0,
+      "step": 35
+    },
+    {
+      "epoch": 0.1362281822051937,
+      "grad_norm": 0.6573143005371094,
+      "learning_rate": 0.00019089874857792946,
+      "loss": 1.3762,
+      "mean_token_accuracy": 0.7971536681056023,
+      "num_tokens": 34497.0,
+      "step": 40
+    },
+    {
+      "epoch": 0.1532567049808429,
+      "grad_norm": 0.6560688614845276,
+      "learning_rate": 0.00018976109215017067,
+      "loss": 1.1589,
+      "mean_token_accuracy": 0.8251897826790809,
+      "num_tokens": 38800.0,
+      "step": 45
+    },
+    {
+      "epoch": 0.17028522775649213,
+      "grad_norm": 0.6654791831970215,
+      "learning_rate": 0.00018862343572241183,
+      "loss": 1.1498,
+      "mean_token_accuracy": 0.8319168403744698,
+      "num_tokens": 43055.0,
+      "step": 50
+    },
+    {
+      "epoch": 0.18731375053214133,
+      "grad_norm": 0.7387417554855347,
+      "learning_rate": 0.00018748577929465302,
+      "loss": 1.1265,
+      "mean_token_accuracy": 0.8290244281291962,
+      "num_tokens": 47346.0,
+      "step": 55
+    },
+    {
+      "epoch": 0.20434227330779056,
+      "grad_norm": 0.5795997977256775,
+      "learning_rate": 0.0001863481228668942,
+      "loss": 1.0046,
+      "mean_token_accuracy": 0.8534704640507698,
+      "num_tokens": 51485.0,
+      "step": 60
+    },
+    {
+      "epoch": 0.22137079608343976,
+      "grad_norm": 0.6834130883216858,
+      "learning_rate": 0.0001852104664391354,
+      "loss": 1.113,
+      "mean_token_accuracy": 0.8345914751291275,
+      "num_tokens": 55716.0,
+      "step": 65
+    },
+    {
+      "epoch": 0.23839931885908897,
+      "grad_norm": 0.7211284041404724,
+      "learning_rate": 0.00018407281001137657,
+      "loss": 1.2132,
+      "mean_token_accuracy": 0.8207321017980576,
+      "num_tokens": 60030.0,
+      "step": 70
+    },
+    {
+      "epoch": 0.2554278416347382,
+      "grad_norm": 0.6312271356582642,
+      "learning_rate": 0.00018293515358361776,
+      "loss": 1.0987,
+      "mean_token_accuracy": 0.8333725541830063,
+      "num_tokens": 64288.0,
+      "step": 75
+    },
+    {
+      "epoch": 0.2724563644103874,
+      "grad_norm": 0.7119404077529907,
+      "learning_rate": 0.00018179749715585894,
+      "loss": 1.0981,
+      "mean_token_accuracy": 0.8323698997497558,
+      "num_tokens": 68548.0,
+      "step": 80
+    },
+    {
+      "epoch": 0.2894848871860366,
+      "grad_norm": 0.9000201225280762,
+      "learning_rate": 0.00018065984072810013,
+      "loss": 1.146,
+      "mean_token_accuracy": 0.8253335595130921,
+      "num_tokens": 72914.0,
+      "step": 85
+    },
+    {
+      "epoch": 0.3065134099616858,
+      "grad_norm": 0.6050537824630737,
+      "learning_rate": 0.0001795221843003413,
+      "loss": 1.0111,
+      "mean_token_accuracy": 0.842674246430397,
+      "num_tokens": 77168.0,
+      "step": 90
+    },
+    {
+      "epoch": 0.32354193273733506,
+      "grad_norm": 0.684512197971344,
+      "learning_rate": 0.0001783845278725825,
+      "loss": 1.1186,
+      "mean_token_accuracy": 0.8351956441998482,
+      "num_tokens": 81439.0,
+      "step": 95
+    },
+    {
+      "epoch": 0.34057045551298426,
+      "grad_norm": 0.7323129773139954,
+      "learning_rate": 0.00017724687144482368,
+      "loss": 1.1287,
+      "mean_token_accuracy": 0.8245970487594605,
+      "num_tokens": 85773.0,
+      "step": 100
+    },
+    {
+      "epoch": 0.35759897828863346,
+      "grad_norm": 0.7547741532325745,
+      "learning_rate": 0.00017610921501706487,
+      "loss": 1.0868,
+      "mean_token_accuracy": 0.8298466548323631,
+      "num_tokens": 90117.0,
+      "step": 105
+    },
+    {
+      "epoch": 0.37462750106428266,
+      "grad_norm": 0.7113769054412842,
+      "learning_rate": 0.00017497155858930602,
+      "loss": 1.1214,
+      "mean_token_accuracy": 0.8299670115113258,
+      "num_tokens": 94412.0,
+      "step": 110
+    },
+    {
+      "epoch": 0.39165602383993187,
+      "grad_norm": 0.7486220002174377,
+      "learning_rate": 0.00017383390216154724,
+      "loss": 1.1452,
+      "mean_token_accuracy": 0.8283886179327965,
+      "num_tokens": 98782.0,
+      "step": 115
+    },
+    {
+      "epoch": 0.4086845466155811,
+      "grad_norm": 0.658633828163147,
+      "learning_rate": 0.0001726962457337884,
+      "loss": 1.0415,
+      "mean_token_accuracy": 0.8431179687380791,
+      "num_tokens": 103011.0,
+      "step": 120
+    },
+    {
+      "epoch": 0.4257130693912303,
+      "grad_norm": 0.783794105052948,
+      "learning_rate": 0.0001715585893060296,
+      "loss": 1.1056,
+      "mean_token_accuracy": 0.8254878520965576,
+      "num_tokens": 107402.0,
+      "step": 125
+    },
+    {
+      "epoch": 0.4427415921668795,
+      "grad_norm": 0.7954565286636353,
+      "learning_rate": 0.00017042093287827076,
+      "loss": 1.0518,
+      "mean_token_accuracy": 0.8375606715679169,
+      "num_tokens": 111707.0,
+      "step": 130
+    },
+    {
+      "epoch": 0.45977011494252873,
+      "grad_norm": 0.6913949847221375,
+      "learning_rate": 0.00016928327645051198,
+      "loss": 1.1104,
+      "mean_token_accuracy": 0.8326424166560173,
+      "num_tokens": 115998.0,
+      "step": 135
+    },
+    {
+      "epoch": 0.47679863771817793,
+      "grad_norm": 0.7918037176132202,
+      "learning_rate": 0.00016814562002275313,
+      "loss": 1.0495,
+      "mean_token_accuracy": 0.8390962019562721,
+      "num_tokens": 120271.0,
+      "step": 140
+    },
+    {
+      "epoch": 0.49382716049382713,
+      "grad_norm": 0.7816826701164246,
+      "learning_rate": 0.00016700796359499432,
+      "loss": 1.0463,
+      "mean_token_accuracy": 0.8433194428682327,
+      "num_tokens": 124461.0,
+      "step": 145
+    },
+    {
+      "epoch": 0.5108556832694764,
+      "grad_norm": 0.8069042563438416,
+      "learning_rate": 0.0001658703071672355,
+      "loss": 1.0664,
+      "mean_token_accuracy": 0.8278923153877258,
+      "num_tokens": 128781.0,
+      "step": 150
+    },
+    {
+      "epoch": 0.5278842060451255,
+      "grad_norm": 1.0114731788635254,
+      "learning_rate": 0.0001647326507394767,
+      "loss": 1.1217,
+      "mean_token_accuracy": 0.8267972275614739,
+      "num_tokens": 133167.0,
+      "step": 155
+    },
+    {
+      "epoch": 0.5449127288207748,
+      "grad_norm": 0.7900378704071045,
+      "learning_rate": 0.00016359499431171787,
+      "loss": 0.971,
+      "mean_token_accuracy": 0.8421565622091294,
+      "num_tokens": 137464.0,
+      "step": 160
+    },
+    {
+      "epoch": 0.561941251596424,
+      "grad_norm": 0.8059927821159363,
+      "learning_rate": 0.00016245733788395906,
+      "loss": 1.0457,
+      "mean_token_accuracy": 0.8381335601210594,
+      "num_tokens": 141760.0,
+      "step": 165
+    },
+    {
+      "epoch": 0.5789697743720732,
+      "grad_norm": 0.7589371800422668,
+      "learning_rate": 0.00016131968145620024,
+      "loss": 1.0208,
+      "mean_token_accuracy": 0.8342296928167343,
+      "num_tokens": 146051.0,
+      "step": 170
+    },
+    {
+      "epoch": 0.5959982971477225,
+      "grad_norm": 0.692416250705719,
+      "learning_rate": 0.00016018202502844143,
+      "loss": 0.9837,
+      "mean_token_accuracy": 0.8510025009512902,
+      "num_tokens": 150270.0,
+      "step": 175
+    },
+    {
+      "epoch": 0.6130268199233716,
+      "grad_norm": 0.6662923097610474,
+      "learning_rate": 0.0001590443686006826,
+      "loss": 0.9835,
+      "mean_token_accuracy": 0.8463438332080842,
+      "num_tokens": 154537.0,
+      "step": 180
+    },
+    {
+      "epoch": 0.6300553426990209,
+      "grad_norm": 0.7452691793441772,
+      "learning_rate": 0.0001579067121729238,
+      "loss": 1.0496,
+      "mean_token_accuracy": 0.8375737622380257,
+      "num_tokens": 158810.0,
+      "step": 185
+    },
+    {
+      "epoch": 0.6470838654746701,
+      "grad_norm": 0.809700608253479,
+      "learning_rate": 0.00015676905574516496,
+      "loss": 1.0595,
+      "mean_token_accuracy": 0.8294038504362107,
+      "num_tokens": 163213.0,
+      "step": 190
+    },
+    {
+      "epoch": 0.6641123882503193,
+      "grad_norm": 0.7708745002746582,
+      "learning_rate": 0.00015563139931740617,
+      "loss": 1.0976,
+      "mean_token_accuracy": 0.8289313957095146,
+      "num_tokens": 167607.0,
+      "step": 195
+    },
+    {
+      "epoch": 0.6811409110259685,
+      "grad_norm": 0.6482141613960266,
+      "learning_rate": 0.00015449374288964733,
+      "loss": 1.0701,
+      "mean_token_accuracy": 0.8261386752128601,
+      "num_tokens": 172024.0,
+      "step": 200
+    },
+    {
+      "epoch": 0.6981694338016177,
+      "grad_norm": 0.7164883613586426,
+      "learning_rate": 0.00015335608646188854,
+      "loss": 0.9878,
+      "mean_token_accuracy": 0.8418964132666588,
+      "num_tokens": 176317.0,
+      "step": 205
+    },
+    {
+      "epoch": 0.7151979565772669,
+      "grad_norm": 0.710343599319458,
+      "learning_rate": 0.0001522184300341297,
+      "loss": 0.9306,
+      "mean_token_accuracy": 0.8468034327030182,
+      "num_tokens": 180558.0,
+      "step": 210
+    },
+    {
+      "epoch": 0.7322264793529162,
+      "grad_norm": 0.863784909248352,
+      "learning_rate": 0.00015108077360637088,
+      "loss": 1.0544,
+      "mean_token_accuracy": 0.8359945684671402,
+      "num_tokens": 184885.0,
+      "step": 215
+    },
+    {
+      "epoch": 0.7492550021285653,
+      "grad_norm": 0.8381637930870056,
+      "learning_rate": 0.00014994311717861207,
+      "loss": 1.0522,
+      "mean_token_accuracy": 0.836811026930809,
+      "num_tokens": 189219.0,
+      "step": 220
+    },
+    {
+      "epoch": 0.7662835249042146,
+      "grad_norm": 0.683501124382019,
+      "learning_rate": 0.00014880546075085325,
+      "loss": 0.9427,
+      "mean_token_accuracy": 0.8544979348778725,
+      "num_tokens": 193437.0,
+      "step": 225
+    },
+    {
+      "epoch": 0.7833120476798637,
+      "grad_norm": 0.7609812617301941,
+      "learning_rate": 0.00014766780432309444,
+      "loss": 1.0048,
+      "mean_token_accuracy": 0.8403829500079155,
+      "num_tokens": 197724.0,
+      "step": 230
+    },
+    {
+      "epoch": 0.800340570455513,
+      "grad_norm": 0.8223949074745178,
+      "learning_rate": 0.00014653014789533562,
+      "loss": 1.078,
+      "mean_token_accuracy": 0.8296335831284523,
+      "num_tokens": 202141.0,
+      "step": 235
+    },
+    {
+      "epoch": 0.8173690932311622,
+      "grad_norm": 0.9807024002075195,
+      "learning_rate": 0.0001453924914675768,
+      "loss": 0.9295,
+      "mean_token_accuracy": 0.8495418474078178,
+      "num_tokens": 206333.0,
+      "step": 240
+    },
+    {
+      "epoch": 0.8343976160068114,
+      "grad_norm": 0.7864217162132263,
+      "learning_rate": 0.000144254835039818,
+      "loss": 1.0326,
+      "mean_token_accuracy": 0.8422158002853394,
+      "num_tokens": 210593.0,
+      "step": 245
+    },
+    {
+      "epoch": 0.8514261387824607,
+      "grad_norm": 0.8183476328849792,
+      "learning_rate": 0.00014311717861205915,
+      "loss": 1.0419,
+      "mean_token_accuracy": 0.8332764700055122,
+      "num_tokens": 214925.0,
+      "step": 250
+    },
+    {
+      "epoch": 0.8684546615581098,
+      "grad_norm": 0.7906543612480164,
+      "learning_rate": 0.00014197952218430036,
+      "loss": 0.9278,
+      "mean_token_accuracy": 0.8531344652175903,
+      "num_tokens": 219106.0,
+      "step": 255
+    },
+    {
+      "epoch": 0.885483184333759,
+      "grad_norm": 0.7864625453948975,
+      "learning_rate": 0.00014084186575654152,
+      "loss": 0.9764,
+      "mean_token_accuracy": 0.8394758701324463,
+      "num_tokens": 223398.0,
+      "step": 260
+    },
+    {
+      "epoch": 0.9025117071094083,
+      "grad_norm": 0.7231821417808533,
+      "learning_rate": 0.00013970420932878273,
+      "loss": 1.0357,
+      "mean_token_accuracy": 0.8368565306067467,
+      "num_tokens": 227720.0,
+      "step": 265
+    },
+    {
+      "epoch": 0.9195402298850575,
+      "grad_norm": 0.7288718223571777,
+      "learning_rate": 0.0001385665529010239,
+      "loss": 1.0178,
+      "mean_token_accuracy": 0.842984040081501,
+      "num_tokens": 232021.0,
+      "step": 270
+    },
+    {
+      "epoch": 0.9365687526607067,
+      "grad_norm": 0.7466130256652832,
+      "learning_rate": 0.0001374288964732651,
+      "loss": 0.9974,
+      "mean_token_accuracy": 0.8431279867887497,
+      "num_tokens": 236312.0,
+      "step": 275
+    },
+    {
+      "epoch": 0.9535972754363559,
+      "grad_norm": 0.7876543402671814,
+      "learning_rate": 0.00013629124004550626,
+      "loss": 1.0057,
+      "mean_token_accuracy": 0.8389794036746026,
+      "num_tokens": 240594.0,
+      "step": 280
+    },
+    {
+      "epoch": 0.9706257982120051,
+      "grad_norm": 0.738293468952179,
+      "learning_rate": 0.00013515358361774744,
+      "loss": 0.9129,
+      "mean_token_accuracy": 0.8528255730867386,
+      "num_tokens": 244859.0,
+      "step": 285
+    },
+    {
+      "epoch": 0.9876543209876543,
+      "grad_norm": 0.8145989775657654,
+      "learning_rate": 0.00013401592718998863,
+      "loss": 0.9188,
+      "mean_token_accuracy": 0.8555046319961548,
+      "num_tokens": 249060.0,
+      "step": 290
+    },
+    {
+      "epoch": 1.0046828437633035,
+      "grad_norm": 0.693233072757721,
+      "learning_rate": 0.00013287827076222981,
+      "loss": 1.0648,
+      "mean_token_accuracy": 0.8477524280548095,
+      "num_tokens": 253361.0,
+      "step": 295
+    },
+    {
+      "epoch": 1.0217113665389528,
+      "grad_norm": 0.8171095848083496,
+      "learning_rate": 0.000131740614334471,
+      "loss": 0.883,
+      "mean_token_accuracy": 0.8561580404639244,
+      "num_tokens": 257633.0,
+      "step": 300
+    },
+    {
+      "epoch": 1.038739889314602,
+      "grad_norm": 0.7343988418579102,
+      "learning_rate": 0.00013060295790671218,
+      "loss": 0.8591,
+      "mean_token_accuracy": 0.8583228841423989,
+      "num_tokens": 261975.0,
+      "step": 305
+    },
+    {
+      "epoch": 1.055768412090251,
+      "grad_norm": 0.6689726114273071,
+      "learning_rate": 0.00012946530147895337,
+      "loss": 0.8397,
+      "mean_token_accuracy": 0.8668102487921715,
+      "num_tokens": 266174.0,
+      "step": 310
+    },
+    {
+      "epoch": 1.0727969348659003,
+      "grad_norm": 0.8284767270088196,
+      "learning_rate": 0.00012832764505119455,
+      "loss": 0.9108,
+      "mean_token_accuracy": 0.8551412716507911,
+      "num_tokens": 270416.0,
+      "step": 315
+    },
+    {
+      "epoch": 1.0898254576415496,
+      "grad_norm": 0.7800877690315247,
+      "learning_rate": 0.0001271899886234357,
+      "loss": 0.923,
+      "mean_token_accuracy": 0.8521544948220253,
+      "num_tokens": 274802.0,
+      "step": 320
+    },
+    {
+      "epoch": 1.1068539804171988,
+      "grad_norm": 0.803035318851471,
+      "learning_rate": 0.00012605233219567692,
+      "loss": 0.9009,
+      "mean_token_accuracy": 0.8583568409085274,
+      "num_tokens": 279061.0,
+      "step": 325
+    },
+    {
+      "epoch": 1.123882503192848,
+      "grad_norm": 0.7928335666656494,
+      "learning_rate": 0.00012491467576791808,
+      "loss": 0.8677,
+      "mean_token_accuracy": 0.860838033258915,
+      "num_tokens": 283290.0,
+      "step": 330
+    },
+    {
+      "epoch": 1.1409110259684971,
+      "grad_norm": 0.82757967710495,
+      "learning_rate": 0.0001237770193401593,
+      "loss": 0.9326,
+      "mean_token_accuracy": 0.8526211172342301,
+      "num_tokens": 287627.0,
+      "step": 335
+    },
+    {
+      "epoch": 1.1579395487441464,
+      "grad_norm": 0.8021914958953857,
+      "learning_rate": 0.00012263936291240045,
+      "loss": 0.9066,
+      "mean_token_accuracy": 0.8505649596452713,
+      "num_tokens": 291975.0,
+      "step": 340
+    },
+    {
+      "epoch": 1.1749680715197957,
+      "grad_norm": 0.7565475106239319,
+      "learning_rate": 0.00012150170648464165,
+      "loss": 0.8812,
+      "mean_token_accuracy": 0.8562570214271545,
+      "num_tokens": 296232.0,
+      "step": 345
+    },
+    {
+      "epoch": 1.191996594295445,
+      "grad_norm": 0.8126978278160095,
+      "learning_rate": 0.00012036405005688282,
+      "loss": 0.905,
+      "mean_token_accuracy": 0.8556828230619431,
+      "num_tokens": 300591.0,
+      "step": 350
+    },
+    {
+      "epoch": 1.2090251170710942,
+      "grad_norm": 0.8174765706062317,
+      "learning_rate": 0.000119226393629124,
+      "loss": 0.9861,
+      "mean_token_accuracy": 0.8424012079834938,
+      "num_tokens": 304998.0,
+      "step": 355
+    },
+    {
+      "epoch": 1.2260536398467432,
+      "grad_norm": 0.8921035528182983,
+      "learning_rate": 0.00011808873720136519,
+      "loss": 0.7724,
+      "mean_token_accuracy": 0.8735315829515458,
+      "num_tokens": 309137.0,
+      "step": 360
+    },
+    {
+      "epoch": 1.2430821626223925,
+      "grad_norm": 0.855992317199707,
+      "learning_rate": 0.00011695108077360638,
+      "loss": 0.8922,
+      "mean_token_accuracy": 0.854039640724659,
+      "num_tokens": 313389.0,
+      "step": 365
+    },
+    {
+      "epoch": 1.2601106853980417,
+      "grad_norm": 0.9408860206604004,
+      "learning_rate": 0.00011581342434584756,
+      "loss": 0.9254,
+      "mean_token_accuracy": 0.8507854476571083,
+      "num_tokens": 317743.0,
+      "step": 370
+    },
+    {
+      "epoch": 1.277139208173691,
+      "grad_norm": 0.7847197651863098,
+      "learning_rate": 0.00011467576791808873,
+      "loss": 0.8563,
+      "mean_token_accuracy": 0.869862625002861,
+      "num_tokens": 321873.0,
+      "step": 375
+    },
+    {
+      "epoch": 1.29416773094934,
+      "grad_norm": 0.8556840419769287,
+      "learning_rate": 0.00011353811149032993,
+      "loss": 0.8489,
+      "mean_token_accuracy": 0.8591933220624923,
+      "num_tokens": 326124.0,
+      "step": 380
+    },
+    {
+      "epoch": 1.3111962537249893,
+      "grad_norm": 0.8849514126777649,
+      "learning_rate": 0.0001124004550625711,
+      "loss": 0.8526,
+      "mean_token_accuracy": 0.8600789621472359,
+      "num_tokens": 330405.0,
+      "step": 385
+    },
+    {
+      "epoch": 1.3282247765006385,
+      "grad_norm": 0.8099865913391113,
+      "learning_rate": 0.00011126279863481229,
+      "loss": 0.9309,
+      "mean_token_accuracy": 0.8511071890592575,
+      "num_tokens": 334701.0,
+      "step": 390
+    },
+    {
+      "epoch": 1.3452532992762878,
+      "grad_norm": 0.8668401837348938,
+      "learning_rate": 0.00011012514220705347,
+      "loss": 0.8671,
+      "mean_token_accuracy": 0.8605618432164193,
+      "num_tokens": 338951.0,
+      "step": 395
+    },
+    {
+      "epoch": 1.362281822051937,
+      "grad_norm": 0.8669872283935547,
+      "learning_rate": 0.00010898748577929466,
+      "loss": 0.8796,
+      "mean_token_accuracy": 0.8592276558279991,
+      "num_tokens": 343203.0,
+      "step": 400
+    },
+    {
+      "epoch": 1.3793103448275863,
+      "grad_norm": 0.8468757271766663,
+      "learning_rate": 0.00010784982935153584,
+      "loss": 0.8941,
+      "mean_token_accuracy": 0.8553030788898468,
+      "num_tokens": 347460.0,
+      "step": 405
+    },
+    {
+      "epoch": 1.3963388676032356,
+      "grad_norm": 0.8839651346206665,
+      "learning_rate": 0.00010671217292377703,
+      "loss": 0.913,
+      "mean_token_accuracy": 0.8489826336503029,
+      "num_tokens": 351850.0,
+      "step": 410
+    },
+    {
+      "epoch": 1.4133673903788846,
+      "grad_norm": 0.8808367848396301,
+      "learning_rate": 0.00010557451649601821,
+      "loss": 0.8158,
+      "mean_token_accuracy": 0.8628147393465042,
+      "num_tokens": 356104.0,
+      "step": 415
+    },
+    {
+      "epoch": 1.4303959131545338,
+      "grad_norm": 0.9303593039512634,
+      "learning_rate": 0.00010443686006825938,
+      "loss": 0.8737,
+      "mean_token_accuracy": 0.8497098922729492,
+      "num_tokens": 360445.0,
+      "step": 420
+    },
+    {
+      "epoch": 1.447424435930183,
+      "grad_norm": 0.7914776802062988,
+      "learning_rate": 0.00010329920364050057,
+      "loss": 0.9168,
+      "mean_token_accuracy": 0.8531492814421654,
+      "num_tokens": 364778.0,
+      "step": 425
+    },
+    {
+      "epoch": 1.4644529587058321,
+      "grad_norm": 0.8661580085754395,
+      "learning_rate": 0.00010216154721274175,
+      "loss": 0.8335,
+      "mean_token_accuracy": 0.8674297228455543,
+      "num_tokens": 368961.0,
+      "step": 430
+    },
+    {
+      "epoch": 1.4814814814814814,
+      "grad_norm": 0.8548939228057861,
+      "learning_rate": 0.00010102389078498294,
+      "loss": 0.9314,
+      "mean_token_accuracy": 0.8409372463822364,
+      "num_tokens": 373355.0,
+      "step": 435
+    },
+    {
+      "epoch": 1.4985100042571307,
+      "grad_norm": 0.8668932914733887,
+      "learning_rate": 9.988623435722412e-05,
+      "loss": 0.8482,
+      "mean_token_accuracy": 0.8576690852642059,
+      "num_tokens": 377652.0,
+      "step": 440
+    },
+    {
+      "epoch": 1.51553852703278,
+      "grad_norm": 0.8412478566169739,
+      "learning_rate": 9.874857792946531e-05,
+      "loss": 0.8791,
+      "mean_token_accuracy": 0.8531419888138772,
+      "num_tokens": 381969.0,
+      "step": 445
+    },
+    {
+      "epoch": 1.5325670498084292,
+      "grad_norm": 0.8298078179359436,
+      "learning_rate": 9.761092150170649e-05,
+      "loss": 0.7418,
+      "mean_token_accuracy": 0.8757623940706253,
+      "num_tokens": 386149.0,
+      "step": 450
+    },
+    {
+      "epoch": 1.5495955725840784,
+      "grad_norm": 0.8505256772041321,
+      "learning_rate": 9.647326507394768e-05,
+      "loss": 0.8107,
+      "mean_token_accuracy": 0.8660028412938118,
+      "num_tokens": 390316.0,
+      "step": 455
+    },
+    {
+      "epoch": 1.5666240953597277,
+      "grad_norm": 0.72185879945755,
+      "learning_rate": 9.533560864618886e-05,
+      "loss": 0.8601,
+      "mean_token_accuracy": 0.8591737478971482,
+      "num_tokens": 394651.0,
+      "step": 460
+    },
+    {
+      "epoch": 1.5836526181353767,
+      "grad_norm": 1.0382378101348877,
+      "learning_rate": 9.419795221843003e-05,
+      "loss": 0.849,
+      "mean_token_accuracy": 0.8591210901737213,
+      "num_tokens": 398879.0,
+      "step": 465
+    },
+    {
+      "epoch": 1.600681140911026,
+      "grad_norm": 0.7781236171722412,
+      "learning_rate": 9.306029579067122e-05,
+      "loss": 0.8587,
+      "mean_token_accuracy": 0.8554968953132629,
+      "num_tokens": 403154.0,
+      "step": 470
+    },
+    {
+      "epoch": 1.617709663686675,
+      "grad_norm": 0.9941114187240601,
+      "learning_rate": 9.19226393629124e-05,
+      "loss": 1.0077,
+      "mean_token_accuracy": 0.8324473947286606,
+      "num_tokens": 407653.0,
+      "step": 475
+    },
+    {
+      "epoch": 1.6347381864623243,
+      "grad_norm": 0.791912853717804,
+      "learning_rate": 9.078498293515359e-05,
+      "loss": 0.8211,
+      "mean_token_accuracy": 0.8655396267771721,
+      "num_tokens": 411904.0,
+      "step": 480
+    },
+    {
+      "epoch": 1.6517667092379735,
+      "grad_norm": 0.8509976267814636,
+      "learning_rate": 8.964732650739477e-05,
+      "loss": 0.8895,
+      "mean_token_accuracy": 0.8587504833936691,
+      "num_tokens": 416159.0,
+      "step": 485
+    },
+    {
+      "epoch": 1.6687952320136228,
+      "grad_norm": 1.0071176290512085,
+      "learning_rate": 8.850967007963596e-05,
+      "loss": 0.9112,
+      "mean_token_accuracy": 0.8539686873555183,
+      "num_tokens": 420513.0,
+      "step": 490
+    },
+    {
+      "epoch": 1.685823754789272,
+      "grad_norm": 0.8273159861564636,
+      "learning_rate": 8.737201365187714e-05,
+      "loss": 0.8383,
+      "mean_token_accuracy": 0.8577379778027534,
+      "num_tokens": 424759.0,
+      "step": 495
+    },
+    {
+      "epoch": 1.7028522775649213,
+      "grad_norm": 0.8064838647842407,
+      "learning_rate": 8.623435722411833e-05,
+      "loss": 0.8397,
+      "mean_token_accuracy": 0.8636475175619125,
+      "num_tokens": 429018.0,
+      "step": 500
+    },
+    {
+      "epoch": 1.7198808003405706,
+      "grad_norm": 0.7176003456115723,
+      "learning_rate": 8.509670079635951e-05,
+      "loss": 0.7738,
+      "mean_token_accuracy": 0.8699946105480194,
+      "num_tokens": 433124.0,
+      "step": 505
+    },
+    {
+      "epoch": 1.7369093231162198,
+      "grad_norm": 0.8316643834114075,
+      "learning_rate": 8.395904436860069e-05,
+      "loss": 0.9191,
+      "mean_token_accuracy": 0.8493718564510345,
+      "num_tokens": 437449.0,
+      "step": 510
+    },
+    {
+      "epoch": 1.7539378458918689,
+      "grad_norm": 0.9423941373825073,
+      "learning_rate": 8.282138794084187e-05,
+      "loss": 0.8749,
+      "mean_token_accuracy": 0.8558909714221954,
+      "num_tokens": 441753.0,
+      "step": 515
+    },
+    {
+      "epoch": 1.770966368667518,
+      "grad_norm": 0.8593487739562988,
+      "learning_rate": 8.168373151308306e-05,
+      "loss": 0.8463,
+      "mean_token_accuracy": 0.857591399550438,
+      "num_tokens": 446036.0,
+      "step": 520
+    },
+    {
+      "epoch": 1.7879948914431671,
+      "grad_norm": 0.7944974303245544,
+      "learning_rate": 8.054607508532424e-05,
+      "loss": 0.8275,
+      "mean_token_accuracy": 0.859096622467041,
+      "num_tokens": 450298.0,
+      "step": 525
+    },
+    {
+      "epoch": 1.8050234142188164,
+      "grad_norm": 0.7622503042221069,
+      "learning_rate": 7.940841865756543e-05,
+      "loss": 0.8846,
+      "mean_token_accuracy": 0.8580268025398254,
+      "num_tokens": 454595.0,
+      "step": 530
+    },
+    {
+      "epoch": 1.8220519369944657,
+      "grad_norm": 0.8578078746795654,
+      "learning_rate": 7.827076222980661e-05,
+      "loss": 0.7674,
+      "mean_token_accuracy": 0.8716912001371384,
+      "num_tokens": 458807.0,
+      "step": 535
+    },
+    {
+      "epoch": 1.839080459770115,
+      "grad_norm": 1.0383292436599731,
+      "learning_rate": 7.71331058020478e-05,
+      "loss": 0.9129,
+      "mean_token_accuracy": 0.8489386543631554,
+      "num_tokens": 463150.0,
+      "step": 540
+    },
+    {
+      "epoch": 1.8561089825457642,
+      "grad_norm": 0.8726801872253418,
+      "learning_rate": 7.599544937428897e-05,
+      "loss": 0.877,
+      "mean_token_accuracy": 0.8568779289722442,
+      "num_tokens": 467472.0,
+      "step": 545
+    },
+    {
+      "epoch": 1.8731375053214134,
+      "grad_norm": 0.9192221164703369,
+      "learning_rate": 7.485779294653015e-05,
+      "loss": 0.9341,
+      "mean_token_accuracy": 0.8403045237064362,
+      "num_tokens": 471930.0,
+      "step": 550
+    },
+    {
+      "epoch": 1.8901660280970627,
+      "grad_norm": 0.8688830137252808,
+      "learning_rate": 7.372013651877134e-05,
+      "loss": 0.8244,
+      "mean_token_accuracy": 0.8679932355880737,
+      "num_tokens": 476140.0,
+      "step": 555
+    },
+    {
+      "epoch": 1.907194550872712,
+      "grad_norm": 0.8286635279655457,
+      "learning_rate": 7.258248009101252e-05,
+      "loss": 0.8725,
+      "mean_token_accuracy": 0.8549414992332458,
+      "num_tokens": 480474.0,
+      "step": 560
+    },
+    {
+      "epoch": 1.924223073648361,
+      "grad_norm": 0.789902925491333,
+      "learning_rate": 7.14448236632537e-05,
+      "loss": 0.8135,
+      "mean_token_accuracy": 0.8649365425109863,
+      "num_tokens": 484805.0,
+      "step": 565
+    },
+    {
+      "epoch": 1.9412515964240102,
+      "grad_norm": 0.8496629595756531,
+      "learning_rate": 7.030716723549489e-05,
+      "loss": 0.9036,
+      "mean_token_accuracy": 0.8460123494267464,
+      "num_tokens": 489275.0,
+      "step": 570
+    },
+    {
+      "epoch": 1.9582801191996593,
+      "grad_norm": 0.8411655426025391,
+      "learning_rate": 6.916951080773608e-05,
+      "loss": 0.9346,
+      "mean_token_accuracy": 0.8429780200123786,
+      "num_tokens": 493726.0,
+      "step": 575
+    },
+    {
+      "epoch": 1.9753086419753085,
+      "grad_norm": 0.8502522706985474,
+      "learning_rate": 6.803185437997726e-05,
+      "loss": 0.8703,
+      "mean_token_accuracy": 0.8595944106578827,
+      "num_tokens": 498022.0,
+      "step": 580
+    },
+    {
+      "epoch": 1.9923371647509578,
+      "grad_norm": 0.743918776512146,
+      "learning_rate": 6.689419795221843e-05,
+      "loss": 0.8815,
+      "mean_token_accuracy": 0.851164074242115,
+      "num_tokens": 502352.0,
+      "step": 585
+    },
+    {
+      "epoch": 2.009365687526607,
+      "grad_norm": 0.7339876294136047,
+      "learning_rate": 6.575654152445962e-05,
+      "loss": 0.9297,
+      "mean_token_accuracy": 0.8610147342085839,
+      "num_tokens": 506669.0,
+      "step": 590
+    },
+    {
+      "epoch": 2.0263942103022563,
+      "grad_norm": 0.903137743473053,
+      "learning_rate": 6.46188850967008e-05,
+      "loss": 0.7306,
+      "mean_token_accuracy": 0.8799364000558854,
+      "num_tokens": 510931.0,
+      "step": 595
+    },
+    {
+      "epoch": 2.0434227330779056,
+      "grad_norm": 0.8741887807846069,
+      "learning_rate": 6.348122866894199e-05,
+      "loss": 0.777,
+      "mean_token_accuracy": 0.8718036338686943,
+      "num_tokens": 515254.0,
+      "step": 600
+    },
+    {
+      "epoch": 2.060451255853555,
+      "grad_norm": 0.9856182932853699,
+      "learning_rate": 6.234357224118317e-05,
+      "loss": 0.6852,
+      "mean_token_accuracy": 0.8851086810231209,
+      "num_tokens": 519444.0,
+      "step": 605
+    },
+    {
+      "epoch": 2.077479778629204,
+      "grad_norm": 0.7548404335975647,
+      "learning_rate": 6.120591581342436e-05,
+      "loss": 0.7239,
+      "mean_token_accuracy": 0.8775098115205765,
+      "num_tokens": 523786.0,
+      "step": 610
+    },
+    {
+      "epoch": 2.0945083014048533,
+      "grad_norm": 1.0486595630645752,
+      "learning_rate": 6.0068259385665536e-05,
+      "loss": 0.7704,
+      "mean_token_accuracy": 0.8707917019724846,
+      "num_tokens": 528181.0,
+      "step": 615
+    },
+    {
+      "epoch": 2.111536824180502,
+      "grad_norm": 0.8551440238952637,
+      "learning_rate": 5.8930602957906714e-05,
+      "loss": 0.7298,
+      "mean_token_accuracy": 0.8771380126476288,
+      "num_tokens": 532472.0,
+      "step": 620
+    },
+    {
+      "epoch": 2.1285653469561514,
+      "grad_norm": 0.7993748784065247,
+      "learning_rate": 5.77929465301479e-05,
+      "loss": 0.7342,
+      "mean_token_accuracy": 0.8784463226795196,
+      "num_tokens": 536780.0,
+      "step": 625
+    },
+    {
+      "epoch": 2.1455938697318007,
+      "grad_norm": 0.9535342454910278,
+      "learning_rate": 5.665529010238908e-05,
+      "loss": 0.7448,
+      "mean_token_accuracy": 0.8769229754805565,
+      "num_tokens": 541096.0,
+      "step": 630
+    },
+    {
+      "epoch": 2.16262239250745,
+      "grad_norm": 0.8289098739624023,
+      "learning_rate": 5.551763367463026e-05,
+      "loss": 0.6921,
+      "mean_token_accuracy": 0.8816722989082336,
+      "num_tokens": 545212.0,
+      "step": 635
+    },
+    {
+      "epoch": 2.179650915283099,
+      "grad_norm": 1.0842015743255615,
+      "learning_rate": 5.437997724687145e-05,
+      "loss": 0.7519,
+      "mean_token_accuracy": 0.87905133664608,
+      "num_tokens": 549486.0,
+      "step": 640
+    },
+    {
+      "epoch": 2.1966794380587484,
+      "grad_norm": 0.9770705699920654,
+      "learning_rate": 5.324232081911263e-05,
+      "loss": 0.7565,
+      "mean_token_accuracy": 0.8737751096487045,
+      "num_tokens": 553849.0,
+      "step": 645
+    },
+    {
+      "epoch": 2.2137079608343977,
+      "grad_norm": 0.9087614417076111,
+      "learning_rate": 5.210466439135382e-05,
+      "loss": 0.7573,
+      "mean_token_accuracy": 0.8769190922379494,
+      "num_tokens": 558157.0,
+      "step": 650
+    },
+    {
+      "epoch": 2.230736483610047,
+      "grad_norm": 0.9485377073287964,
+      "learning_rate": 5.0967007963594995e-05,
+      "loss": 0.7951,
+      "mean_token_accuracy": 0.8717585399746894,
+      "num_tokens": 562499.0,
+      "step": 655
+    },
+    {
+      "epoch": 2.247765006385696,
+      "grad_norm": 0.901766300201416,
+      "learning_rate": 4.982935153583618e-05,
+      "loss": 0.7584,
+      "mean_token_accuracy": 0.8740618869662284,
+      "num_tokens": 566735.0,
+      "step": 660
+    },
+    {
+      "epoch": 2.264793529161345,
+      "grad_norm": 0.9577491879463196,
+      "learning_rate": 4.8691695108077365e-05,
+      "loss": 0.8409,
+      "mean_token_accuracy": 0.8705617383122444,
+      "num_tokens": 571024.0,
+      "step": 665
+    },
+    {
+      "epoch": 2.2818220519369943,
+      "grad_norm": 0.791725218296051,
+      "learning_rate": 4.755403868031855e-05,
+      "loss": 0.6348,
+      "mean_token_accuracy": 0.8875991255044937,
+      "num_tokens": 575196.0,
+      "step": 670
+    },
+    {
+      "epoch": 2.2988505747126435,
+      "grad_norm": 1.0129467248916626,
+      "learning_rate": 4.641638225255973e-05,
+      "loss": 0.7094,
+      "mean_token_accuracy": 0.8820217370986938,
+      "num_tokens": 579384.0,
+      "step": 675
+    },
+    {
+      "epoch": 2.315879097488293,
+      "grad_norm": 0.9562749266624451,
+      "learning_rate": 4.527872582480091e-05,
+      "loss": 0.7119,
+      "mean_token_accuracy": 0.8796836137771606,
+      "num_tokens": 583637.0,
+      "step": 680
+    },
+    {
+      "epoch": 2.332907620263942,
+      "grad_norm": 0.8766334056854248,
+      "learning_rate": 4.41410693970421e-05,
+      "loss": 0.779,
+      "mean_token_accuracy": 0.8700046718120575,
+      "num_tokens": 588005.0,
+      "step": 685
+    },
+    {
+      "epoch": 2.3499361430395913,
+      "grad_norm": 0.9728025794029236,
+      "learning_rate": 4.300341296928328e-05,
+      "loss": 0.8319,
+      "mean_token_accuracy": 0.8586345180869103,
+      "num_tokens": 592448.0,
+      "step": 690
+    },
+    {
+      "epoch": 2.3669646658152406,
+      "grad_norm": 1.0943338871002197,
+      "learning_rate": 4.186575654152446e-05,
+      "loss": 0.7845,
+      "mean_token_accuracy": 0.8698052436113357,
+      "num_tokens": 596703.0,
+      "step": 695
+    },
+    {
+      "epoch": 2.38399318859089,
+      "grad_norm": 1.1211864948272705,
+      "learning_rate": 4.0728100113765646e-05,
+      "loss": 0.7837,
+      "mean_token_accuracy": 0.8664575144648552,
+      "num_tokens": 601127.0,
+      "step": 700
+    },
+    {
+      "epoch": 2.401021711366539,
+      "grad_norm": 0.9164478182792664,
+      "learning_rate": 3.959044368600683e-05,
+      "loss": 0.708,
+      "mean_token_accuracy": 0.8818950295448303,
+      "num_tokens": 605371.0,
+      "step": 705
+    },
+    {
+      "epoch": 2.4180502341421883,
+      "grad_norm": 1.0944688320159912,
+      "learning_rate": 3.8452787258248016e-05,
+      "loss": 0.8541,
+      "mean_token_accuracy": 0.8556552082300186,
+      "num_tokens": 609890.0,
+      "step": 710
+    },
+    {
+      "epoch": 2.4350787569178376,
+      "grad_norm": 0.8398585319519043,
+      "learning_rate": 3.7315130830489194e-05,
+      "loss": 0.7117,
+      "mean_token_accuracy": 0.882653883099556,
+      "num_tokens": 614025.0,
+      "step": 715
+    },
+    {
+      "epoch": 2.4521072796934864,
+      "grad_norm": 0.9557759165763855,
+      "learning_rate": 3.617747440273038e-05,
+      "loss": 0.7401,
+      "mean_token_accuracy": 0.8780117958784104,
+      "num_tokens": 618268.0,
+      "step": 720
+    },
+    {
+      "epoch": 2.4691358024691357,
+      "grad_norm": 0.7890902757644653,
+      "learning_rate": 3.5039817974971564e-05,
+      "loss": 0.7193,
+      "mean_token_accuracy": 0.8795603841543198,
+      "num_tokens": 622542.0,
+      "step": 725
+    },
+    {
+      "epoch": 2.486164325244785,
+      "grad_norm": 1.0514216423034668,
+      "learning_rate": 3.390216154721274e-05,
+      "loss": 0.6987,
+      "mean_token_accuracy": 0.8816746294498443,
+      "num_tokens": 626771.0,
+      "step": 730
+    },
+    {
+      "epoch": 2.503192848020434,
+      "grad_norm": 1.0042310953140259,
+      "learning_rate": 3.276450511945393e-05,
+      "loss": 0.7099,
+      "mean_token_accuracy": 0.8860125571489335,
+      "num_tokens": 630981.0,
+      "step": 735
+    },
+    {
+      "epoch": 2.5202213707960834,
+      "grad_norm": 1.0508288145065308,
+      "learning_rate": 3.162684869169511e-05,
+      "loss": 0.7424,
+      "mean_token_accuracy": 0.8739517882466317,
+      "num_tokens": 635240.0,
+      "step": 740
+    },
+    {
+      "epoch": 2.5372498935717327,
+      "grad_norm": 1.0945532321929932,
+      "learning_rate": 3.0489192263936294e-05,
+      "loss": 0.8181,
+      "mean_token_accuracy": 0.8624349996447563,
+      "num_tokens": 639694.0,
+      "step": 745
+    },
+    {
+      "epoch": 2.554278416347382,
+      "grad_norm": 0.9198687076568604,
+      "learning_rate": 2.9351535836177476e-05,
+      "loss": 0.688,
+      "mean_token_accuracy": 0.880143529176712,
+      "num_tokens": 643984.0,
+      "step": 750
+    },
+    {
+      "epoch": 2.571306939123031,
+      "grad_norm": 1.0412315130233765,
+      "learning_rate": 2.8213879408418657e-05,
+      "loss": 0.6844,
+      "mean_token_accuracy": 0.8923282608389854,
+      "num_tokens": 648166.0,
+      "step": 755
+    },
+    {
+      "epoch": 2.58833546189868,
+      "grad_norm": 0.9161568284034729,
+      "learning_rate": 2.7076222980659842e-05,
+      "loss": 0.7436,
+      "mean_token_accuracy": 0.8677403450012207,
+      "num_tokens": 652487.0,
+      "step": 760
+    },
+    {
+      "epoch": 2.6053639846743293,
+      "grad_norm": 0.7734108567237854,
+      "learning_rate": 2.5938566552901024e-05,
+      "loss": 0.6938,
+      "mean_token_accuracy": 0.8824578642845153,
+      "num_tokens": 656735.0,
+      "step": 765
+    },
+    {
+      "epoch": 2.6223925074499785,
+      "grad_norm": 1.2506450414657593,
+      "learning_rate": 2.480091012514221e-05,
+      "loss": 0.7896,
+      "mean_token_accuracy": 0.8708192393183708,
+      "num_tokens": 661125.0,
+      "step": 770
+    },
+    {
+      "epoch": 2.639421030225628,
+      "grad_norm": 0.9822338223457336,
+      "learning_rate": 2.366325369738339e-05,
+      "loss": 0.7611,
+      "mean_token_accuracy": 0.8697439581155777,
+      "num_tokens": 665455.0,
+      "step": 775
+    },
+    {
+      "epoch": 2.656449553001277,
+      "grad_norm": 1.0660203695297241,
+      "learning_rate": 2.2525597269624575e-05,
+      "loss": 0.8025,
+      "mean_token_accuracy": 0.867020557820797,
+      "num_tokens": 669868.0,
+      "step": 780
+    },
+    {
+      "epoch": 2.6734780757769263,
+      "grad_norm": 1.049364686012268,
+      "learning_rate": 2.138794084186576e-05,
+      "loss": 0.7601,
+      "mean_token_accuracy": 0.8773441627621651,
+      "num_tokens": 674152.0,
+      "step": 785
+    },
+    {
+      "epoch": 2.6905065985525756,
+      "grad_norm": 0.9868401288986206,
+      "learning_rate": 2.025028441410694e-05,
+      "loss": 0.7507,
+      "mean_token_accuracy": 0.8820523858070374,
+      "num_tokens": 678390.0,
+      "step": 790
+    },
+    {
+      "epoch": 2.707535121328225,
+      "grad_norm": 0.9983195662498474,
+      "learning_rate": 1.9112627986348127e-05,
+      "loss": 0.7143,
+      "mean_token_accuracy": 0.8788602381944657,
+      "num_tokens": 682664.0,
+      "step": 795
+    },
+    {
+      "epoch": 2.724563644103874,
+      "grad_norm": 0.8293647170066833,
+      "learning_rate": 1.7974971558589308e-05,
+      "loss": 0.7131,
+      "mean_token_accuracy": 0.8797033429145813,
+      "num_tokens": 686921.0,
+      "step": 800
+    }
+  ],
+  "logging_steps": 5,
+  "max_steps": 879,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 3,
+  "save_steps": 200,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 6438561661903872.0,
+  "train_batch_size": 1,
+  "trial_name": null,
+  "trial_params": null
+}

checkpoint-800/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:001de43419a04313fd3d652571d90911489fbcebf2f0e7c3f8aa624286dfc855
+size 5624

checkpoint-879/README.md

@@ -0,0 +1,209 @@
+---
+base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.20.0

checkpoint-879/adapter_config.json

@@ -0,0 +1,50 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "monteclora_config": null,
+  "peft_type": "LORA",
+  "peft_version": "0.20.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "up_proj",
+    "down_proj",
+    "k_proj",
+    "o_proj",
+    "v_proj",
+    "gate_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false,
+  "velora_config": null
+}