Mistral-7B-Instruct-v0.2-ORPO-SALT
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the dpo_mix_en and the bct_non_cot_dpo_1000 datasets. It achieves the following results on the evaluation set:
- Loss: 0.8630
- Rewards/chosen: -0.0798
- Rewards/rejected: -0.1033
- Rewards/accuracies: 0.5618
- Rewards/margins: 0.0235
- Logps/rejected: -1.0328
- Logps/chosen: -0.7975
- Logits/rejected: -2.8558
- Logits/chosen: -2.8473
- Sft Loss: 0.7975
- Odds Ratio Loss: 0.6547
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 3.0
Training results
Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Sft Loss | Odds Ratio Loss |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0.93 | 0.8082 | 500 | 0.8928 | -0.0828 | -0.1057 | 0.5773 | 0.0229 | -1.0567 | -0.8278 | -2.8442 | -2.8368 | 0.8278 | 0.6496 |
0.7571 | 1.6165 | 1000 | 0.8679 | -0.0803 | -0.1034 | 0.5700 | 0.0231 | -1.0337 | -0.8028 | -2.8729 | -2.8644 | 0.8028 | 0.6510 |
0.8035 | 2.4247 | 1500 | 0.8630 | -0.0798 | -0.1033 | 0.5618 | 0.0235 | -1.0328 | -0.7975 | -2.8558 | -2.8473 | 0.7975 | 0.6547 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1
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