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--- |
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library_name: transformers |
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license: mit |
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base_model: gpt2 |
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tags: |
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- trl |
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- dpo |
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- generated_from_trainer |
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model-index: |
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- name: nlp-a5 |
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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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# nlp-a5 |
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on [`distilabel-intel-orca-dpo-pairs`](https://huggingface.co/datasets/argilla/distilabel-intel-orca-dpo-pairs) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6409 |
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- Rewards/chosen: 0.9778 |
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- Rewards/rejected: -2.1491 |
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- Rewards/accuracies: 0.8235 |
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- Rewards/margins: 3.1270 |
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- Logps/rejected: -410.6469 |
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- Logps/chosen: -337.3829 |
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- Logits/rejected: -66.9816 |
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- Logits/chosen: -67.8481 |
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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: 5.38e-05 |
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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: 4 |
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- total_train_batch_size: 32 |
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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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- lr_scheduler_warmup_steps: 50 |
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- training_steps: 500 |
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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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| 0.6454 | 0.1382 | 50 | 0.7701 | 0.4667 | -1.3878 | 0.7591 | 1.8546 | -406.8403 | -339.9385 | -95.7163 | -95.3393 | |
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| 0.7265 | 0.2764 | 100 | 0.7531 | 0.2791 | -2.1548 | 0.7777 | 2.4339 | -410.6752 | -340.8765 | -85.4456 | -85.2691 | |
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| 0.5317 | 0.4147 | 150 | 0.7164 | 0.0401 | -2.6230 | 0.7743 | 2.6631 | -413.0164 | -342.0717 | -77.7900 | -78.4781 | |
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| 0.8947 | 0.5529 | 200 | 0.7223 | -0.0327 | -3.1585 | 0.7961 | 3.1258 | -415.6938 | -342.4356 | -73.7223 | -74.3845 | |
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| 0.6882 | 0.6911 | 250 | 0.6677 | 0.6186 | -2.0402 | 0.7904 | 2.6588 | -410.1023 | -339.1790 | -66.4183 | -67.2267 | |
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| 0.4596 | 0.8293 | 300 | 0.6199 | 0.5863 | -2.4937 | 0.8116 | 3.0800 | -412.3698 | -339.3405 | -66.5151 | -67.2825 | |
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| 0.6719 | 0.9675 | 350 | 0.6214 | 1.1018 | -1.4390 | 0.7842 | 2.5408 | -407.0965 | -336.7633 | -64.9415 | -65.8130 | |
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| 0.119 | 1.1057 | 400 | 0.6442 | 0.4069 | -2.8694 | 0.8282 | 3.2763 | -414.2482 | -340.2375 | -64.6611 | -65.4554 | |
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| 0.1427 | 1.2440 | 450 | 0.6730 | 1.1133 | -1.9897 | 0.8131 | 3.1030 | -409.8499 | -336.7056 | -65.8348 | -66.7287 | |
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| 0.1022 | 1.3822 | 500 | 0.6409 | 0.9778 | -2.1491 | 0.8235 | 3.1270 | -410.6469 | -337.3829 | -66.9816 | -67.8481 | |
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### Framework versions |
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- Transformers 4.45.0 |
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- Pytorch 2.4.0+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.20.3 |
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