zephyr-7b-dpo-qlora
This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-qlora on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.6813
- Rewards/chosen: -0.0009
- Rewards/rejected: -0.0252
- Rewards/accuracies: 0.2920
- Rewards/margins: 0.0243
- Logps/rejected: -71.3009
- Logps/chosen: -65.4449
- Logits/rejected: -2.4428
- Logits/chosen: -2.4444
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
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 8
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.69 | 0.26 | 100 | 0.6897 | 0.0232 | 0.0168 | 0.2680 | 0.0064 | -67.1001 | -63.0342 | -2.4904 | -2.4911 |
| 0.6869 | 0.52 | 200 | 0.6849 | 0.0066 | -0.0092 | 0.3060 | 0.0159 | -69.7060 | -64.6950 | -2.4556 | -2.4573 |
| 0.681 | 0.78 | 300 | 0.6815 | -0.0026 | -0.0264 | 0.2880 | 0.0238 | -71.4280 | -65.6224 | -2.4430 | -2.4446 |
Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.14.6
- Tokenizers 0.15.2
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Model tree for lole25/zephyr-7b-dpo-qlora
Base model
mistralai/Mistral-7B-v0.1