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--- |
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base_model: lvwerra/gpt2-imdb |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: gpt-imdb-fkl-beta_0.1 |
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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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# gpt-imdb-fkl-beta_0.1 |
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This model is a fine-tuned version of [lvwerra/gpt2-imdb](https://huggingface.co/lvwerra/gpt2-imdb) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Step: 7000 |
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- Loss: 43157476.0 |
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- Rewards/chosen: 0.2870 |
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- Rewards/rejected: -0.3647 |
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- Rewards/accuracies: 0.7750 |
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- Rewards/margins: 0.6517 |
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- Logps/rejected: -267.3319 |
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- Logps/chosen: -232.3951 |
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- Logits/rejected: -35.4871 |
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- Logits/chosen: -35.8462 |
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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: 1e-05 |
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- train_batch_size: 24 |
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- eval_batch_size: 24 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 150 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
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|:-------------:|:-----:|:----:|:---------------------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 0.6613 | 0.21 | 500 | 1870813158870725165056.0000 | 0.4663 | 0.2817 | 0.5937 | 0.1846 | -260.8683 | -230.6020 | -34.4235 | -34.9404 | |
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| 0.5684 | 0.42 | 1000 | 147.6206 | 0.5625 | 0.2263 | 0.6708 | 0.3362 | -261.4219 | -229.6398 | -32.2534 | -32.7960 | |
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| 0.5548 | 0.63 | 1500 | 387.0789 | 0.7744 | 0.4004 | 0.6417 | 0.3740 | -259.6809 | -227.5212 | -35.6332 | -36.0763 | |
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| 0.7404 | 0.83 | 2000 | 306766.0 | 0.6319 | 0.1306 | 0.6792 | 0.5013 | -262.3793 | -228.9465 | -35.7930 | -36.3250 | |
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| 0.3854 | 1.04 | 2500 | 104512616.0 | 0.3906 | -0.2340 | 0.7354 | 0.6245 | -266.0248 | -231.3594 | -37.8272 | -38.3586 | |
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| 0.5825 | 1.25 | 3000 | 6146.4980 | 0.6931 | 0.1933 | 0.7063 | 0.4999 | -261.7526 | -228.3339 | -36.5475 | -37.0416 | |
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| 2792.03 | 1.46 | 3500 | 5439941120.0 | 0.4414 | -0.1668 | 0.7271 | 0.6082 | -265.3533 | -230.8516 | -37.3611 | -37.9083 | |
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| 11.3378 | 1.67 | 4000 | 1371221.625 | 0.5757 | -0.0709 | 0.7438 | 0.6465 | -264.3939 | -229.5085 | -36.9220 | -37.3953 | |
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| 1.9493 | 1.88 | 4500 | 181183.6875 | 0.5196 | -0.0750 | 0.7437 | 0.5947 | -264.4354 | -230.0688 | -36.8487 | -37.2339 | |
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| 1.4785 | 2.08 | 5000 | 18712162.0 | 0.3104 | -0.3569 | 0.7750 | 0.6673 | -267.2543 | -232.1608 | -35.5673 | -35.9495 | |
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| 0.4516 | 2.29 | 5500 | 3858633.25 | 0.3507 | -0.2764 | 0.7604 | 0.6272 | -266.4495 | -231.7578 | -35.4563 | -35.8284 | |
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| 0.3984 | 2.5 | 6000 | 61627688.0 | 0.2498 | -0.4039 | 0.7792 | 0.6537 | -267.7244 | -232.7677 | -35.1970 | -35.5582 | |
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| 93.8127 | 2.71 | 6500 | 67355640.0 | 0.2917 | -0.3600 | 0.7708 | 0.6517 | -267.2854 | -232.3483 | -35.4841 | -35.8434 | |
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| 4472.7729 | 2.92 | 7000 | 43157476.0 | 0.2870 | -0.3647 | 0.7750 | 0.6517 | -267.3319 | -232.3951 | -35.4871 | -35.8462 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.1 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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