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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: selective-pairrm-33079692-mt2 |
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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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# selective-pairrm-33079692-mt2 |
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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: 0.7212 |
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- Rewards/chosen: -2.3879 |
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- Rewards/rejected: -2.5044 |
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- Rewards/accuracies: 0.5742 |
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- Rewards/margins: 0.1164 |
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- Logps/rejected: -817.7779 |
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- Logps/chosen: -781.7959 |
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- Logits/rejected: -3.0082 |
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- Logits/chosen: -3.0229 |
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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: 4 |
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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: 4 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- total_eval_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: 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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| 0.3678 | 0.32 | 100 | 0.8166 | -3.5115 | -3.6302 | 0.5703 | 0.1186 | -930.3584 | -894.1545 | -3.2211 | -3.2330 | |
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| 0.5115 | 0.64 | 200 | 0.7558 | -2.9722 | -3.0863 | 0.5781 | 0.1141 | -875.9759 | -840.2244 | -2.8707 | -2.8897 | |
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| 0.6156 | 0.96 | 300 | 0.7196 | -2.3861 | -2.5020 | 0.5703 | 0.1159 | -817.5390 | -781.6083 | -3.0086 | -3.0233 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.14.6 |
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- Tokenizers 0.15.0 |
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