Delete pretrain_tokens/wandb

pretrain_tokens/wandb/debug-internal.log

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pretrain_tokens/wandb/debug.log

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pretrain_tokens/wandb/run-20260409_024256-4yonu3x2/files/config.yaml

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pretrain_tokens/wandb/run-20260409_024256-4yonu3x2/files/output.log

@@ -1,268 +0,0 @@
-04/09/2026 02:42:57 - WARNING - __main__ - Process rank: 0, device: cuda:0, n_gpu: 1, distributed training: False, 16-bits training: False
-04/09/2026 02:42:57 - INFO - __main__ - Training/evaluation parameters TrainingArguments(
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-)
-Using custom data configuration default-9aa68439a1bf4533
-04/09/2026 02:42:58 - INFO - datasets.builder - Using custom data configuration default-9aa68439a1bf4533
-Generating dataset csv (/home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420)
-04/09/2026 02:42:58 - INFO - datasets.builder - Generating dataset csv (/home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420)
-Downloading and preparing dataset csv/default to /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420...
-04/09/2026 02:42:58 - INFO - datasets.builder - Downloading and preparing dataset csv/default to /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420...
-Downloading took 0.0 min
-04/09/2026 02:42:58 - INFO - datasets.download.download_manager - Downloading took 0.0 min
-Checksum Computation took 0.0 min
-04/09/2026 02:42:58 - INFO - datasets.download.download_manager - Checksum Computation took 0.0 min
-Generating train split
-04/09/2026 02:42:58 - INFO - datasets.builder - Generating train split
-Generating train split: 982503 examples [00:24, 40012.03 examples/s]
-Generating validation split
-04/09/2026 02:43:22 - INFO - datasets.builder - Generating validation split
-Generating validation split: 109173 examples [00:02, 40132.11 examples/s]
-Unable to verify splits sizes.
-04/09/2026 02:43:25 - INFO - datasets.utils.info_utils - Unable to verify splits sizes.
-Dataset csv downloaded and prepared to /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420. Subsequent calls will reuse this data.
-04/09/2026 02:43:25 - INFO - datasets.builder - Dataset csv downloaded and prepared to /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420. Subsequent calls will reuse this data.
-[INFO|configuration_utils.py:715] 2026-04-09 02:43:25,496 >> loading configuration file /home/n5huang/dna_token/pretrain/models/len2_5120/config.json
-[INFO|configuration_utils.py:777] 2026-04-09 02:43:25,497 >> Model config BertConfig {
-  "architectures": [
-    "BertForMaskedLM"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "hidden_act": "gelu",
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-  "hidden_size": 768,
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "layer_norm_eps": 1e-12,
-  "max_length": 512,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "pad_token_id": 0,
-  "position_embedding_type": "absolute",
-  "torch_dtype": "float32",
-  "transformers_version": "4.35.2",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 5120
-}
-04/09/2026 02:43:25 - INFO - __main__ - Training new model from scratch
-
-/home/n5huang/miniconda3/envs/bpe/lib/python3.9/site-packages/transformers/utils/generic.py:309: FutureWarning: `torch.utils._pytree._register_pytree_node` is deprecated. Please use `torch.utils._pytree.register_pytree_node` instead.
-  _torch_pytree._register_pytree_node(
-[INFO|configuration_utils.py:791] 2026-04-09 02:43:25,507 >> Generate config GenerationConfig {
-  "max_length": 512,
-  "pad_token_id": 0
-}
-
-Process #1 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-b7e4e83b1e5bb0f0_00000_of_00008.arrow
-04/09/2026 02:43:41 - INFO - datasets.arrow_dataset - Process #1 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-b7e4e83b1e5bb0f0_00000_of_00008.arrow
-Process #2 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-b7e4e83b1e5bb0f0_00001_of_00008.arrow
-04/09/2026 02:43:41 - INFO - datasets.arrow_dataset - Process #2 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-b7e4e83b1e5bb0f0_00001_of_00008.arrow
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-04/09/2026 02:43:41 - INFO - datasets.arrow_dataset - Process #3 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-b7e4e83b1e5bb0f0_00002_of_00008.arrow
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-04/09/2026 02:43:41 - INFO - datasets.arrow_dataset - Process #4 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-b7e4e83b1e5bb0f0_00003_of_00008.arrow
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-04/09/2026 02:43:41 - INFO - datasets.arrow_dataset - Process #5 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-b7e4e83b1e5bb0f0_00004_of_00008.arrow
-Process #6 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-b7e4e83b1e5bb0f0_00005_of_00008.arrow
-04/09/2026 02:43:41 - INFO - datasets.arrow_dataset - Process #6 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-b7e4e83b1e5bb0f0_00005_of_00008.arrow
-Process #7 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-b7e4e83b1e5bb0f0_00006_of_00008.arrow
-04/09/2026 02:43:41 - INFO - datasets.arrow_dataset - Process #7 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-b7e4e83b1e5bb0f0_00006_of_00008.arrow
-Process #8 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-b7e4e83b1e5bb0f0_00007_of_00008.arrow
-04/09/2026 02:43:41 - INFO - datasets.arrow_dataset - Process #8 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-b7e4e83b1e5bb0f0_00007_of_00008.arrow
-Running tokenizer on dataset line_by_line (num_proc=8):   0%|          | 0/982503 [00:00<?, ? examples/s]Spawning 8 processes
-04/09/2026 02:43:41 - INFO - datasets.arrow_dataset - Spawning 8 processes
-Running tokenizer on dataset line_by_line (num_proc=8): 100%|██████████| 982503/982503 [02:32<00:00, 6449.24 examples/s]
-Concatenating 8 shards
-04/09/2026 02:46:14 - INFO - datasets.arrow_dataset - Concatenating 8 shards
-Process #1 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-e09c066770dc1f08_00000_of_00008.arrow
-04/09/2026 02:46:14 - INFO - datasets.arrow_dataset - Process #1 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-e09c066770dc1f08_00000_of_00008.arrow
-Process #2 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-e09c066770dc1f08_00001_of_00008.arrow
-04/09/2026 02:46:14 - INFO - datasets.arrow_dataset - Process #2 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-e09c066770dc1f08_00001_of_00008.arrow
-Process #3 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-e09c066770dc1f08_00002_of_00008.arrow
-04/09/2026 02:46:14 - INFO - datasets.arrow_dataset - Process #3 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-e09c066770dc1f08_00002_of_00008.arrow
-Process #4 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-e09c066770dc1f08_00003_of_00008.arrow
-04/09/2026 02:46:14 - INFO - datasets.arrow_dataset - Process #4 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-e09c066770dc1f08_00003_of_00008.arrow
-Process #5 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-e09c066770dc1f08_00004_of_00008.arrow
-04/09/2026 02:46:14 - INFO - datasets.arrow_dataset - Process #5 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-e09c066770dc1f08_00004_of_00008.arrow
-Process #6 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-e09c066770dc1f08_00005_of_00008.arrow
-04/09/2026 02:46:14 - INFO - datasets.arrow_dataset - Process #6 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-e09c066770dc1f08_00005_of_00008.arrow
-Process #7 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-e09c066770dc1f08_00006_of_00008.arrow
-04/09/2026 02:46:14 - INFO - datasets.arrow_dataset - Process #7 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-e09c066770dc1f08_00006_of_00008.arrow
-Process #8 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-e09c066770dc1f08_00007_of_00008.arrow
-04/09/2026 02:46:14 - INFO - datasets.arrow_dataset - Process #8 will write at /home/n5huang/dna_token/output_tokens/cache/csv/default-9aa68439a1bf4533/0.0.0/a43390c7ecea6519ff2ce9d10005c8750601c9e456069be5efbd2747df45f420/cache-e09c066770dc1f08_00007_of_00008.arrow
-Running tokenizer on dataset line_by_line (num_proc=8):   0%|          | 0/109173 [00:00<?, ? examples/s]Spawning 8 processes
-04/09/2026 02:46:14 - INFO - datasets.arrow_dataset - Spawning 8 processes
-Running tokenizer on dataset line_by_line (num_proc=8): 100%|██████████| 109173/109173 [00:17<00:00, 6162.84 examples/s]
-Concatenating 8 shards
-04/09/2026 02:46:31 - INFO - datasets.arrow_dataset - Concatenating 8 shards
-[INFO|trainer.py:544] 2026-04-09 02:46:37,686 >> max_steps is given, it will override any value given in num_train_epochs
-[INFO|trainer.py:2066] 2026-04-09 02:46:37,688 >> Loading model from /home/n5huang/dna_token/pretrain/models/len2_5120/checkpoint-100000.
-[WARNING|trainer.py:2231] 2026-04-09 02:46:37,942 >> There were missing keys in the checkpoint model loaded: ['cls.predictions.decoder.weight', 'cls.predictions.decoder.bias'].
-[INFO|trainer.py:738] 2026-04-09 02:46:38,250 >> The following columns in the training set don't have a corresponding argument in `BertForMaskedLM.forward` and have been ignored: special_tokens_mask. If special_tokens_mask are not expected by `BertForMaskedLM.forward`,  you can safely ignore this message.
-[INFO|trainer.py:1723] 2026-04-09 02:46:38,922 >> ***** Running training *****
-[INFO|trainer.py:1724] 2026-04-09 02:46:38,923 >>   Num examples = 982,503
-[INFO|trainer.py:1725] 2026-04-09 02:46:38,923 >>   Num Epochs = 10
-[INFO|trainer.py:1726] 2026-04-09 02:46:38,924 >>   Instantaneous batch size per device = 96
-[INFO|trainer.py:1729] 2026-04-09 02:46:38,924 >>   Total train batch size (w. parallel, distributed & accumulation) = 96
-[INFO|trainer.py:1730] 2026-04-09 02:46:38,925 >>   Gradient Accumulation steps = 1
-[INFO|trainer.py:1731] 2026-04-09 02:46:38,925 >>   Total optimization steps = 100,000
-[INFO|trainer.py:1732] 2026-04-09 02:46:38,926 >>   Number of trainable parameters = 89,980,160
-[INFO|trainer.py:1752] 2026-04-09 02:46:38,927 >>   Continuing training from checkpoint, will skip to saved global_step
-[INFO|trainer.py:1753] 2026-04-09 02:46:38,927 >>   Continuing training from epoch 9
-[INFO|trainer.py:1754] 2026-04-09 02:46:38,927 >>   Continuing training from global step 100000
-[INFO|trainer.py:1756] 2026-04-09 02:46:38,927 >>   Will skip the first 9 epochs then the first 7885 batches in the first epoch.
-[INFO|integration_utils.py:718] 2026-04-09 02:46:38,928 >> Automatic Weights & Biases logging enabled, to disable set os.environ["WANDB_DISABLED"] = "true"
-  0%|          | 0/100000 [00:00<?, ?it/s][WARNING|logging.py:314] 2026-04-09 02:46:40,535 >> You're using a PreTrainedTokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.
-[INFO|trainer.py:2302] 2026-04-09 02:46:41,283 >> Didn't find an RNG file, if you are resuming a training that was launched in a distributed fashion, reproducibility is not guaranteed.
-100001it [00:04, 20981.36it/s]            [INFO|trainer.py:1955] 2026-04-09 02:46:43,723 >>
-
-Training completed. Do not forget to share your model on huggingface.co/models =)
-
-
-100001it [00:04, 20868.88it/s]
-{'train_runtime': 4.7982, 'train_samples_per_second': 2000761.461, 'train_steps_per_second': 20841.265, 'train_loss': 4.9309695196505064e-05, 'epoch': 9.77}
-[INFO|trainer.py:2881] 2026-04-09 02:46:43,749 >> Saving model checkpoint to /home/n5huang/dna_token/pretrain/models/len2_5120
-[INFO|configuration_utils.py:461] 2026-04-09 02:46:43,751 >> Configuration saved in /home/n5huang/dna_token/pretrain/models/len2_5120/config.json
-[INFO|configuration_utils.py:564] 2026-04-09 02:46:43,752 >> Configuration saved in /home/n5huang/dna_token/pretrain/models/len2_5120/generation_config.json
-[INFO|modeling_utils.py:2193] 2026-04-09 02:46:44,597 >> Model weights saved in /home/n5huang/dna_token/pretrain/models/len2_5120/pytorch_model.bin
-***** train metrics *****
-  epoch                    =        9.77
-  train_loss               =         0.0
-  train_runtime            =  0:00:04.79
-  train_samples            =      982503
-  train_samples_per_second = 2000761.461
-  train_steps_per_second   =   20841.265
-04/09/2026 02:46:44 - INFO - __main__ - *** Evaluate ***
-[INFO|trainer.py:738] 2026-04-09 02:46:44,604 >> The following columns in the evaluation set don't have a corresponding argument in `BertForMaskedLM.forward` and have been ignored: special_tokens_mask. If special_tokens_mask are not expected by `BertForMaskedLM.forward`,  you can safely ignore this message.
-[INFO|trainer.py:3158] 2026-04-09 02:46:44,623 >> ***** Running Evaluation *****
-[INFO|trainer.py:3160] 2026-04-09 02:46:44,623 >>   Num examples = 109173
-[INFO|trainer.py:3163] 2026-04-09 02:46:44,623 >>   Batch size = 96
-100%|██████████| 1138/1138 [20:09<00:00,  1.06s/it]
-***** eval metrics *****
-  epoch                   =       9.77
-  eval_accuracy           =     0.2987
-  eval_loss               =     4.9606
-  eval_runtime            = 0:20:10.53
-  eval_samples            =     109173
-  eval_samples_per_second =     90.186
-  eval_step               =     100001
-  eval_steps_per_second   =       0.94
-  perplexity              =   142.6779
-[INFO|modelcard.py:452] 2026-04-09 03:06:55,252 >> Dropping the following result as it does not have all the necessary fields:
-{'task': {'name': 'Masked Language Modeling', 'type': 'fill-mask'}, 'metrics': [{'name': 'Accuracy', 'type': 'accuracy', 'value': 0.2987349408299944}]}

pretrain_tokens/wandb/run-20260409_024256-4yonu3x2/files/requirements.txt

@@ -1,148 +0,0 @@
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-torch==2.8.0
-protobuf==3.20.3
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pretrain_tokens/wandb/run-20260409_024256-4yonu3x2/files/wandb-metadata.json

@@ -1,149 +0,0 @@
-{
-  "os":  "Linux-5.15.0-72-generic-x86_64-with-glibc2.35",
-  "python":  "CPython 3.9.18",
-  "startedAt":  "2026-04-09T02:42:56.385921Z",
-  "args":  [
-    "--output_dir",
-    "/home/n5huang/dna_token/pretrain/models/len2_5120",
-    "--model_type",
-    "bert",
-    "--tokenizer_name",
-    "/home/n5huang/dna_token/tokenizer_evaluation/merge_bpe/vocab_5120/merge_tokenizer_unigram_len2.json",
-    "--config_name",
-    "/home/n5huang/dna_token/pretrain/models/len2_5120/config.json",
-    "--project_name",
-    "token_eval_len2_5120",
-    "--do_train",
-    "True",
-    "--model_max_length",
-    "512",
-    "--max_seq_length",
-    "512",
-    "--line_by_line",
-    "True",
-    "--pad_to_max_length",
-    "True",
-    "--train_file",
-    "/home/n5huang/dna_token/output_tokens/merge_bpe_5120_allchr_all_tokenized_train_chrOnly.tsv",
-    "--validation_file",
-    "/home/n5huang/dna_token/output_tokens/merge_bpe_5120_allchr_all_tokenized_val_chrOnly.tsv",
-    "--cache_dir",
-    "/home/n5huang/dna_token/output_tokens/cache",
-    "--use_fast_tokenizer",
-    "True",
-    "--do_eval",
-    "True",
-    "--gradient_accumulation_steps",
-    "1",
-    "--per_device_train_batch_size",
-    "96",
-    "--per_device_eval_batch_size",
-    "96",
-    "--save_steps",
-    "1000",
-    "--save_total_limit",
-    "10",
-    "--max_steps",
-    "100000",
-    "--logging_steps",
-    "1000",
-    "--learning_rate",
-    "4e-5",
-    "--adam_epsilon",
-    "1e-6",
-    "--weight_decay",
-    "0.01",
-    "--adam_beta1",
-    "0.9",
-    "--adam_beta2",
-    "0.98",
-    "--mlm_probability",
-    "0.15",
-    "--warmup_steps",
-    "10000",
-    "--seed",
-    "42",
-    "--preprocessing_num_workers",
-    "8",
-    "--resume_from_checkpoint",
-    "/home/n5huang/dna_token/pretrain/models/len2_5120/checkpoint-100000"
-  ],
-  "program":  "/home/n5huang/dna-tokenizer/BPE_merge/run_mlm_200k.py",
-  "email":  "mtapiapacheco@ucsd.edu",
-  "root":  "/data/n5huang/dna_token/output_tokens",
-  "host":  "sn4622116170",
-  "executable":  "/home/n5huang/miniconda3/envs/bpe/bin/python",
-  "cpu_count":  128,
-  "cpu_count_logical":  255,
-  "gpu":  "NVIDIA A100 80GB PCIe",
-  "gpu_count":  8,
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-  "gpu_nvidia":  [
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-      "architecture":  "Ampere",
-      "uuid":  "GPU-dc4eaee8-f907-9592-417e-e0dbe37f86a3"
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-2026-04-12 03:29:56,516 INFO    wandb-AsyncioManager-main:3566905 [mailbox.py:close():137] Closing mailbox, abandoning 1 handles.

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