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--- |
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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: zephyr-7b-dpo-full |
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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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# zephyr-7b-dpo-full |
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This model was trained from scratch on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4292 |
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- Rewards/chosen: -1.8869 |
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- Rewards/rejected: -2.7914 |
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- Rewards/accuracies: 0.8242 |
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- Rewards/margins: 0.9045 |
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- Logps/rejected: -612.2493 |
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- Logps/chosen: -524.2042 |
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- Logits/rejected: -0.4436 |
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- Logits/chosen: -0.8025 |
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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-07 |
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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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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 64 |
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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_ratio: 0.1 |
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- num_epochs: 1 |
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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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| 0.5405 | 0.12 | 100 | 0.6086 | -0.8599 | -1.1867 | 0.6953 | 0.3268 | -451.7755 | -421.5048 | -1.6547 | -1.7462 | |
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| 0.4371 | 0.23 | 200 | 0.5454 | -2.0208 | -2.5842 | 0.7422 | 0.5634 | -591.5291 | -537.5920 | -0.7151 | -0.8867 | |
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| 0.4348 | 0.35 | 300 | 0.5012 | -2.0998 | -2.8410 | 0.7734 | 0.7413 | -617.2101 | -545.4883 | -0.3499 | -0.5939 | |
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| 0.3733 | 0.46 | 400 | 0.4721 | -2.1506 | -2.9308 | 0.7773 | 0.7802 | -626.1902 | -550.5717 | -0.2280 | -0.5456 | |
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| 0.3689 | 0.58 | 500 | 0.4484 | -2.0467 | -2.9485 | 0.7969 | 0.9018 | -627.9595 | -540.1826 | -0.1091 | -0.4774 | |
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| 0.3829 | 0.69 | 600 | 0.4419 | -2.0265 | -2.9075 | 0.8086 | 0.8810 | -623.8541 | -538.1624 | -0.1412 | -0.5099 | |
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| 0.3725 | 0.81 | 700 | 0.4329 | -1.9184 | -2.8079 | 0.8242 | 0.8895 | -613.8932 | -527.3496 | -0.3224 | -0.6920 | |
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| 0.4052 | 0.92 | 800 | 0.4292 | -1.8869 | -2.7914 | 0.8242 | 0.9045 | -612.2493 | -524.2042 | -0.4436 | -0.8025 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.2+cu118 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.2 |
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