| --- |
| license: mit |
| base_model: gpt2 |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: BASE_short |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # BASE_short |
| |
| This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 3.3241 |
| - Ppl: 28.7555 |
| |
| ## Model description |
| |
| More information needed |
| |
| ## Intended uses & limitations |
| |
| More information needed |
| |
| ## Training and evaluation data |
| |
| More information needed |
| |
| ## Training procedure |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - learning_rate: 0.0001 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - seed: 22554 |
| - distributed_type: multi-GPU |
| - gradient_accumulation_steps: 8 |
| - total_train_batch_size: 32 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 2000 |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Ppl | |
| |:-------------:|:-----:|:-----:|:---------------:|:-------:| |
| | 4.4673 | 1.25 | 4000 | 4.2416 | 71.9939 | |
| | 3.8603 | 2.5 | 8000 | 3.7253 | 43.0163 | |
| | 3.638 | 3.75 | 12000 | 3.5322 | 35.4396 | |
| | 3.5229 | 5.01 | 16000 | 3.4322 | 32.0556 | |
| | 3.4377 | 6.26 | 20000 | 3.3749 | 30.2611 | |
| | 3.3972 | 7.51 | 24000 | 3.3411 | 29.2534 | |
| | 3.3688 | 8.76 | 28000 | 3.3241 | 28.7555 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.35.0.dev0 |
| - Pytorch 1.13.1+cu117 |
| - Datasets 2.14.6 |
| - Tokenizers 0.14.1 |
|
|
