mistral-dpo
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5536
- Rewards/chosen: 0.2363
- Rewards/rejected: -0.3821
- Rewards/accuracies: 0.7095
- Rewards/margins: 0.6183
- Logps/rejected: -278.2731
- Logps/chosen: -292.0563
- Logits/rejected: -2.6610
- Logits/chosen: -2.7000
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: 4
- seed: 100
- 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
- num_epochs: 1.0
Training results
Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
---|---|---|---|---|---|---|---|---|---|---|---|
0.5093 | 1.0 | 625 | 0.5536 | 0.2363 | -0.3821 | 0.7095 | 0.6183 | -278.2731 | -292.0563 | -2.6610 | -2.7000 |
Framework versions
- PEFT 0.7.2.dev0
- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.1
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Model tree for smangrul/mistral-dpo
Base model
mistralai/Mistral-7B-v0.1