| --- |
| license: mit |
| library_name: peft |
| tags: |
| - trl |
| - sft |
| - generated_from_trainer |
| base_model: Aravindan/gpt2out |
| datasets: |
| - generator |
| model-index: |
| - name: output_dir |
| 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. --> |
|
|
| # output_dir |
| |
| This model is a fine-tuned version of [Aravindan/gpt2out](https://huggingface.co/Aravindan/gpt2out) on the generator dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.9619 |
| |
| ## 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: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 10 |
| - total_train_batch_size: 80 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: constant |
| - training_steps: 1000 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 2.6318 | 0.0147 | 30 | 2.4202 | |
| | 2.5147 | 0.0294 | 60 | 2.3425 | |
| | 2.4599 | 0.0440 | 90 | 2.2838 | |
| | 2.4009 | 0.0587 | 120 | 2.2386 | |
| | 2.394 | 0.0734 | 150 | 2.1971 | |
| | 2.3459 | 0.0881 | 180 | 2.1614 | |
| | 2.3057 | 0.1027 | 210 | 2.1324 | |
| | 2.3085 | 0.1174 | 240 | 2.1076 | |
| | 2.2675 | 0.1321 | 270 | 2.0891 | |
| | 2.2348 | 0.1468 | 300 | 2.0716 | |
| | 2.2167 | 0.1614 | 330 | 2.0594 | |
| | 2.1827 | 0.1761 | 360 | 2.0481 | |
| | 2.2049 | 0.1908 | 390 | 2.0390 | |
| | 2.1803 | 0.2055 | 420 | 2.0303 | |
| | 2.1709 | 0.2201 | 450 | 2.0250 | |
| | 2.1915 | 0.2348 | 480 | 2.0183 | |
| | 2.1583 | 0.2495 | 510 | 2.0120 | |
| | 2.168 | 0.2642 | 540 | 2.0072 | |
| | 2.1678 | 0.2788 | 570 | 2.0026 | |
| | 2.1545 | 0.2935 | 600 | 1.9988 | |
| | 2.1561 | 0.3082 | 630 | 1.9941 | |
| | 2.1442 | 0.3229 | 660 | 1.9913 | |
| | 2.1393 | 0.3375 | 690 | 1.9867 | |
| | 2.1489 | 0.3522 | 720 | 1.9834 | |
| | 2.1304 | 0.3669 | 750 | 1.9814 | |
| | 2.1175 | 0.3816 | 780 | 1.9783 | |
| | 2.113 | 0.3962 | 810 | 1.9753 | |
| | 2.1025 | 0.4109 | 840 | 1.9729 | |
| | 2.1181 | 0.4256 | 870 | 1.9711 | |
| | 2.0947 | 0.4403 | 900 | 1.9688 | |
| | 2.0868 | 0.4549 | 930 | 1.9665 | |
| | 2.1061 | 0.4696 | 960 | 1.9638 | |
| | 2.1096 | 0.4843 | 990 | 1.9619 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.11.1 |
| - Transformers 4.41.2 |
| - Pytorch 2.1.2 |
| - Datasets 2.19.2 |
| - Tokenizers 0.19.1 |
