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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-alpha_0.3-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-alpha_0.3-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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- Loss: 25.4567 |
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- Rewards/chosen: -0.2859 |
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- Rewards/rejected: -1.2893 |
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- Rewards/accuracies: 0.8458 |
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- Rewards/margins: 1.0034 |
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- Logps/rejected: -276.5780 |
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- Logps/chosen: -238.1245 |
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- Logits/rejected: -31.6823 |
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- Logits/chosen: -32.1973 |
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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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| 0.3872 | 0.21 | 500 | 0.9032 | -0.0063 | -0.4921 | 0.7833 | 0.4858 | -268.6066 | -235.3286 | -32.2910 | -32.9554 | |
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| 0.937 | 0.42 | 1000 | 0.5782 | 0.3739 | -0.2273 | 0.7667 | 0.6012 | -265.9586 | -231.5264 | -33.2571 | -33.9060 | |
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| 1.6799 | 0.63 | 1500 | 3.1537 | 0.2527 | -0.4167 | 0.7729 | 0.6694 | -267.8524 | -232.7385 | -33.1089 | -33.5974 | |
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| 0.8141 | 0.83 | 2000 | 1.8978 | 0.1800 | -0.6646 | 0.7917 | 0.8446 | -270.3312 | -233.4657 | -32.3310 | -32.9275 | |
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| 0.4758 | 1.04 | 2500 | 7.5225 | 0.0635 | -0.8693 | 0.8188 | 0.9329 | -272.3785 | -234.6298 | -32.0571 | -32.5700 | |
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| 0.5184 | 1.25 | 3000 | 2.2710 | 0.3736 | -0.5136 | 0.8021 | 0.8872 | -268.8213 | -231.5289 | -33.9791 | -34.4883 | |
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| 0.3571 | 1.46 | 3500 | 12.0724 | 0.0389 | -0.9119 | 0.8125 | 0.9507 | -272.8040 | -234.8766 | -32.0986 | -32.6149 | |
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| 1.8478 | 1.67 | 4000 | 14.8072 | 0.0021 | -0.9754 | 0.8229 | 0.9775 | -273.4396 | -235.2442 | -32.4363 | -32.9745 | |
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| 0.6874 | 1.88 | 4500 | 5.9952 | 0.0487 | -0.9284 | 0.8167 | 0.9771 | -272.9694 | -234.7781 | -32.9101 | -33.4694 | |
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| 0.2233 | 2.08 | 5000 | 11.0797 | -0.2853 | -1.2611 | 0.8479 | 0.9758 | -276.2962 | -238.1182 | -31.8450 | -32.3602 | |
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| 0.1784 | 2.29 | 5500 | 7.9899 | -0.1567 | -1.1325 | 0.8375 | 0.9757 | -275.0099 | -236.8327 | -32.0292 | -32.5741 | |
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| 0.2919 | 2.5 | 6000 | 29.0523 | -0.3295 | -1.3283 | 0.8500 | 0.9988 | -276.9686 | -238.5604 | -31.4315 | -31.9371 | |
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| 2.011 | 2.71 | 6500 | 28.3221 | -0.2974 | -1.3018 | 0.8458 | 1.0044 | -276.7031 | -238.2393 | -31.6565 | -32.1763 | |
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| 1.7899 | 2.92 | 7000 | 25.4567 | -0.2859 | -1.2893 | 0.8458 | 1.0034 | -276.5780 | -238.1245 | -31.6823 | -32.1973 | |
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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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