mistral-7b-dpo-full-wo-kqa_silver_wogold-ep3
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.2946
- Rewards/chosen: -2.2047
- Rewards/rejected: -5.9058
- Rewards/accuracies: 0.8793
- Rewards/margins: 3.7012
- Logps/rejected: -1521.8148
- Logps/chosen: -750.3969
- Logits/rejected: -3.0916
- Logits/chosen: -3.2432
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-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.1362 | 0.65 | 100 | -3.2790 | -3.1123 | -721.5319 | -1477.7874 | 0.3206 | 0.8707 | -1.9160 | 3.5495 | -5.4655 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2
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