mistral-7b-dpo-full-sft-wo-kqa_silver_wogold
This model is a fine-tuned version of Minbyul/mistral-7b-wo-kqa_silver_wogold-sft on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.0530
- Rewards/chosen: -2.4760
- Rewards/rejected: -21.0723
- Rewards/accuracies: 0.9700
- Rewards/margins: 18.5963
- Logps/rejected: -2709.2131
- Logps/chosen: -407.7003
- Logits/rejected: -2.0225
- Logits/chosen: -2.2276
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 | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.2735 | 0.32 | 100 | 0.0529 | -1.3592 | -8.1857 | 0.9700 | 6.8265 | -1420.5509 | -296.0260 | -2.7457 | -2.5375 |
| 0.1321 | 0.63 | 200 | 0.0507 | -2.0405 | -16.8511 | 0.9600 | 14.8106 | -2287.0967 | -364.1557 | -2.2518 | -2.3349 |
| 0.117 | 0.95 | 300 | 0.0531 | -2.4855 | -21.1345 | 0.9700 | 18.6490 | -2715.4331 | -408.6504 | -2.0210 | -2.2273 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2
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