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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: 1.3947 |
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- Rewards/chosen: -2.4314 |
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- Rewards/rejected: -2.0023 |
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- Rewards/accuracies: 0.3867 |
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- Rewards/margins: -0.4292 |
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- Logps/rejected: -517.7516 |
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- Logps/chosen: -554.9180 |
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- Logits/rejected: -1.0823 |
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- Logits/chosen: -1.1239 |
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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 | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected | |
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|:-------------:|:-----:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:| |
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| 0.3047 | 0.1 | 100 | -2.4405 | -2.3863 | -361.0801 | -337.7748 | 0.8551 | 0.3203 | -0.4930 | -0.2905 | -0.2025 | |
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| 0.1861 | 0.21 | 200 | -1.5418 | -1.5107 | -450.2716 | -421.0934 | 1.0495 | 0.3867 | -1.3850 | -0.3493 | -1.0357 | |
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| 0.1608 | 0.31 | 300 | -1.4367 | -1.4022 | -454.9446 | -422.9684 | 1.0910 | 0.3945 | -1.4317 | -0.3772 | -1.0544 | |
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| 0.1368 | 0.42 | 400 | -1.0538 | -1.0131 | -520.1699 | -479.6456 | 1.3010 | 0.4102 | -2.0839 | -0.4627 | -1.6212 | |
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| 0.1364 | 0.52 | 500 | -1.6466 | -1.6090 | -470.0934 | -430.8614 | 1.1773 | 0.3711 | -1.5832 | -0.4498 | -1.1334 | |
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| 0.1223 | 0.63 | 600 | 1.3206 | -2.2971 | -1.8297 | 0.4141 | -0.4674 | -500.4930 | -541.4883 | -1.1541 | -1.1880 | |
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| 0.0971 | 0.73 | 700 | 1.4638 | -2.6554 | -2.1594 | 0.3906 | -0.4959 | -533.4667 | -577.3128 | -0.9392 | -0.9712 | |
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| 0.1035 | 0.84 | 800 | 1.4475 | -2.5761 | -2.1538 | 0.3945 | -0.4222 | -532.9068 | -569.3817 | -0.8902 | -0.9232 | |
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| 0.088 | 0.94 | 900 | 1.3947 | -2.4314 | -2.0023 | 0.3867 | -0.4292 | -517.7516 | -554.9180 | -1.0823 | -1.1239 | |
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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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