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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: training |
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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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# training |
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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: 0.4649 |
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- Rewards/chosen: 1.1097 |
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- Rewards/rejected: 0.3323 |
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- Rewards/accuracies: 0.8186 |
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- Rewards/margins: 0.7774 |
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- Logps/rejected: -143.4800 |
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- Logps/chosen: -175.0714 |
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- Logits/rejected: -35.2043 |
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- Logits/chosen: -32.7114 |
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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: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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: linear |
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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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| No log | 0.55 | 400 | 0.6593 | 1.0074 | 0.5904 | 0.7357 | 0.4170 | -140.8990 | -176.0949 | -35.9356 | -33.1922 | |
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| 0.7974 | 1.11 | 800 | 0.5807 | 1.1511 | 0.5902 | 0.7634 | 0.5610 | -140.9016 | -174.6575 | -35.9192 | -33.2655 | |
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| 0.5983 | 1.66 | 1200 | 0.5200 | 1.0697 | 0.4300 | 0.7979 | 0.6397 | -142.5030 | -175.4720 | -35.5696 | -33.0300 | |
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| 0.4982 | 2.21 | 1600 | 0.4807 | 1.1128 | 0.3733 | 0.8158 | 0.7395 | -143.0704 | -175.0409 | -35.2967 | -32.7791 | |
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| 0.4663 | 2.77 | 2000 | 0.4649 | 1.1097 | 0.3323 | 0.8186 | 0.7774 | -143.4800 | -175.0714 | -35.2043 | -32.7114 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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