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--- |
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license: mit |
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library_name: peft |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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base_model: Aravindan/gpt2out |
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datasets: |
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- generator |
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model-index: |
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- name: output_dir |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# output_dir |
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This model is a fine-tuned version of [Aravindan/gpt2out](https://huggingface.co/Aravindan/gpt2out) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9619 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 10 |
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- total_train_batch_size: 80 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant |
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- training_steps: 1000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.6318 | 0.0147 | 30 | 2.4202 | |
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| 2.5147 | 0.0294 | 60 | 2.3425 | |
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| 2.4599 | 0.0440 | 90 | 2.2838 | |
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| 2.4009 | 0.0587 | 120 | 2.2386 | |
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| 2.394 | 0.0734 | 150 | 2.1971 | |
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| 2.3459 | 0.0881 | 180 | 2.1614 | |
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| 2.3057 | 0.1027 | 210 | 2.1324 | |
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| 2.3085 | 0.1174 | 240 | 2.1076 | |
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| 2.2675 | 0.1321 | 270 | 2.0891 | |
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| 2.2348 | 0.1468 | 300 | 2.0716 | |
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| 2.2167 | 0.1614 | 330 | 2.0594 | |
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| 2.1827 | 0.1761 | 360 | 2.0481 | |
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| 2.2049 | 0.1908 | 390 | 2.0390 | |
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| 2.1803 | 0.2055 | 420 | 2.0303 | |
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| 2.1709 | 0.2201 | 450 | 2.0250 | |
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| 2.1915 | 0.2348 | 480 | 2.0183 | |
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| 2.1583 | 0.2495 | 510 | 2.0120 | |
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| 2.168 | 0.2642 | 540 | 2.0072 | |
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| 2.1678 | 0.2788 | 570 | 2.0026 | |
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| 2.1545 | 0.2935 | 600 | 1.9988 | |
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| 2.1561 | 0.3082 | 630 | 1.9941 | |
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| 2.1442 | 0.3229 | 660 | 1.9913 | |
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| 2.1393 | 0.3375 | 690 | 1.9867 | |
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| 2.1489 | 0.3522 | 720 | 1.9834 | |
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| 2.1304 | 0.3669 | 750 | 1.9814 | |
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| 2.1175 | 0.3816 | 780 | 1.9783 | |
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| 2.113 | 0.3962 | 810 | 1.9753 | |
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| 2.1025 | 0.4109 | 840 | 1.9729 | |
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| 2.1181 | 0.4256 | 870 | 1.9711 | |
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| 2.0947 | 0.4403 | 900 | 1.9688 | |
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| 2.0868 | 0.4549 | 930 | 1.9665 | |
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| 2.1061 | 0.4696 | 960 | 1.9638 | |
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| 2.1096 | 0.4843 | 990 | 1.9619 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
