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--- |
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license: llama3 |
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base_model: tsavage68/Summary_L3_1000steps_1e7rate_SFT2 |
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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: Summary_L3_1000steps_1e6rate_03beta_CSFTDPO |
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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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# Summary_L3_1000steps_1e6rate_03beta_CSFTDPO |
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This model is a fine-tuned version of [tsavage68/Summary_L3_1000steps_1e7rate_SFT2](https://huggingface.co/tsavage68/Summary_L3_1000steps_1e7rate_SFT2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5961 |
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- Rewards/chosen: 0.0294 |
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- Rewards/rejected: -2.5656 |
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- Rewards/accuracies: 0.1400 |
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- Rewards/margins: 2.5950 |
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- Logps/rejected: -23.8158 |
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- Logps/chosen: -9.2849 |
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- Logits/rejected: -1.1435 |
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- Logits/chosen: -1.1436 |
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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-06 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 4 |
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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: 100 |
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- training_steps: 1000 |
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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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| 0.5553 | 0.2004 | 50 | 0.5962 | 0.0778 | -1.2696 | 0.1400 | 1.3473 | -19.4956 | -9.1236 | -1.1038 | -1.1053 | |
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| 0.6585 | 0.4008 | 100 | 0.5962 | 0.0854 | -1.4439 | 0.1400 | 1.5292 | -20.0766 | -9.0982 | -1.1078 | -1.1092 | |
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| 0.6238 | 0.6012 | 150 | 0.5961 | 0.0687 | -2.1556 | 0.1400 | 2.2243 | -22.4490 | -9.1538 | -1.1298 | -1.1306 | |
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| 0.6065 | 0.8016 | 200 | 0.5961 | 0.0322 | -2.5726 | 0.1400 | 2.6048 | -23.8390 | -9.2754 | -1.1437 | -1.1438 | |
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| 0.6238 | 1.0020 | 250 | 0.5961 | 0.0294 | -2.5678 | 0.1400 | 2.5971 | -23.8230 | -9.2849 | -1.1438 | -1.1440 | |
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| 0.6238 | 1.2024 | 300 | 0.5961 | 0.0279 | -2.5674 | 0.1400 | 2.5953 | -23.8219 | -9.2899 | -1.1439 | -1.1440 | |
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| 0.6238 | 1.4028 | 350 | 0.5961 | 0.0304 | -2.5648 | 0.1400 | 2.5952 | -23.8131 | -9.2814 | -1.1438 | -1.1439 | |
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| 0.5718 | 1.6032 | 400 | 0.5961 | 0.0304 | -2.5648 | 0.1400 | 2.5952 | -23.8131 | -9.2814 | -1.1438 | -1.1439 | |
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| 0.5892 | 1.8036 | 450 | 0.5961 | 0.0338 | -2.5715 | 0.1400 | 2.6052 | -23.8353 | -9.2702 | -1.1435 | -1.1436 | |
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| 0.5718 | 2.0040 | 500 | 0.5961 | 0.0279 | -2.5720 | 0.1400 | 2.5999 | -23.8372 | -9.2897 | -1.1434 | -1.1435 | |
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| 0.5718 | 2.2044 | 550 | 0.5961 | 0.0266 | -2.5750 | 0.1400 | 2.6016 | -23.8472 | -9.2942 | -1.1438 | -1.1440 | |
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| 0.5545 | 2.4048 | 600 | 0.5961 | 0.0271 | -2.5761 | 0.1400 | 2.6032 | -23.8507 | -9.2925 | -1.1438 | -1.1440 | |
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| 0.5199 | 2.6052 | 650 | 0.5961 | 0.0271 | -2.5761 | 0.1400 | 2.6032 | -23.8507 | -9.2925 | -1.1438 | -1.1440 | |
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| 0.6238 | 2.8056 | 700 | 0.5961 | 0.0270 | -2.5764 | 0.1400 | 2.6035 | -23.8519 | -9.2928 | -1.1438 | -1.1440 | |
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| 0.6065 | 3.0060 | 750 | 0.5961 | 0.0315 | -2.5674 | 0.1400 | 2.5989 | -23.8216 | -9.2777 | -1.1434 | -1.1436 | |
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| 0.6412 | 3.2064 | 800 | 0.5961 | 0.0276 | -2.5662 | 0.1400 | 2.5937 | -23.8176 | -9.2909 | -1.1434 | -1.1436 | |
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| 0.6585 | 3.4068 | 850 | 0.5961 | 0.0277 | -2.5666 | 0.1400 | 2.5943 | -23.8191 | -9.2903 | -1.1434 | -1.1436 | |
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| 0.6238 | 3.6072 | 900 | 0.5961 | 0.0281 | -2.5670 | 0.1400 | 2.5952 | -23.8205 | -9.2891 | -1.1434 | -1.1436 | |
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| 0.5372 | 3.8076 | 950 | 0.5961 | 0.0310 | -2.5656 | 0.1400 | 2.5966 | -23.8159 | -9.2795 | -1.1435 | -1.1436 | |
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| 0.6238 | 4.0080 | 1000 | 0.5961 | 0.0294 | -2.5656 | 0.1400 | 2.5950 | -23.8158 | -9.2849 | -1.1435 | -1.1436 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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