| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: openai-community/gpt2-medium |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: tinystories_upsampled_tom |
| | 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. --> |
| |
|
| | [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ptsvil/tom-training/runs/t2roxoo7) |
| | # tinystories_upsampled_tom |
| |
|
| | This model is a fine-tuned version of [openai-community/gpt2-medium](https://huggingface.co/openai-community/gpt2-medium) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.6461 |
| |
|
| | ## 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: 32 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 8 |
| | - total_train_batch_size: 256 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 1 |
| | - num_epochs: 3 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:-----:|:---------------:| |
| | | 1.8989 | 0.1051 | 400 | 1.8900 | |
| | | 1.8563 | 0.2102 | 800 | 1.8378 | |
| | | 1.8476 | 0.3153 | 1200 | 1.7993 | |
| | | 1.8063 | 0.4204 | 1600 | 1.7859 | |
| | | 1.7846 | 0.5255 | 2000 | 1.7627 | |
| | | 1.7625 | 0.6306 | 2400 | 1.7536 | |
| | | 1.7617 | 0.7357 | 2800 | 1.7368 | |
| | | 1.7527 | 0.8408 | 3200 | 1.7257 | |
| | | 1.7714 | 0.9459 | 3600 | 1.7172 | |
| | | 1.6993 | 1.0510 | 4000 | 1.7162 | |
| | | 1.6844 | 1.1561 | 4400 | 1.7071 | |
| | | 1.6898 | 1.2612 | 4800 | 1.7007 | |
| | | 1.6678 | 1.3663 | 5200 | 1.6925 | |
| | | 1.7036 | 1.4714 | 5600 | 1.6887 | |
| | | 1.6849 | 1.5765 | 6000 | 1.6817 | |
| | | 1.6781 | 1.6816 | 6400 | 1.6764 | |
| | | 1.6228 | 1.7867 | 6800 | 1.6712 | |
| | | 1.6467 | 1.8918 | 7200 | 1.6679 | |
| | | 1.6672 | 1.9969 | 7600 | 1.6619 | |
| | | 1.6092 | 2.1020 | 8000 | 1.6652 | |
| | | 1.6181 | 2.2071 | 8400 | 1.6615 | |
| | | 1.6183 | 2.3122 | 8800 | 1.6566 | |
| | | 1.6101 | 2.4173 | 9200 | 1.6573 | |
| | | 1.6009 | 2.5224 | 9600 | 1.6515 | |
| | | 1.6002 | 2.6275 | 10000 | 1.6520 | |
| | | 1.6387 | 2.7326 | 10400 | 1.6497 | |
| | | 1.6401 | 2.8377 | 10800 | 1.6477 | |
| | | 1.6186 | 2.9428 | 11200 | 1.6466 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.44.1 |
| | - Pytorch 2.2.2 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.19.1 |
| |
|
