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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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datasets: |
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- generator |
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model-index: |
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- name: gpt2-dp-mod-datasets-txt-processing |
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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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# gpt2-dp-mod-datasets-txt-processing |
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.3134 |
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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: 0.0005 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 1000 |
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- num_epochs: 6 |
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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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| 6.694 | 0.28 | 500 | 5.6630 | |
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| 5.3512 | 0.55 | 1000 | 5.2372 | |
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| 5.0119 | 0.83 | 1500 | 4.9763 | |
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| 4.767 | 1.1 | 2000 | 4.8279 | |
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| 4.5688 | 1.38 | 2500 | 4.7089 | |
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| 4.4767 | 1.65 | 3000 | 4.6105 | |
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| 4.3893 | 1.93 | 3500 | 4.5220 | |
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| 4.1792 | 2.21 | 4000 | 4.4846 | |
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| 4.1211 | 2.48 | 4500 | 4.4302 | |
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| 4.08 | 2.76 | 5000 | 4.3699 | |
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| 4.0158 | 3.03 | 5500 | 4.3318 | |
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| 3.7873 | 3.31 | 6000 | 4.3214 | |
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| 3.7888 | 3.58 | 6500 | 4.2912 | |
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| 3.7709 | 3.86 | 7000 | 4.2590 | |
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| 3.6276 | 4.13 | 7500 | 4.2642 | |
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| 3.4947 | 4.41 | 8000 | 4.2579 | |
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| 3.4884 | 4.69 | 8500 | 4.2439 | |
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| 3.4836 | 4.96 | 9000 | 4.2315 | |
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| 3.3261 | 5.24 | 9500 | 4.2430 | |
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| 3.2961 | 5.51 | 10000 | 4.2427 | |
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| 3.2947 | 5.79 | 10500 | 4.2419 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.13.0 |
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- Tokenizers 0.13.3 |
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