metadata
library_name: peft
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: zephyr-7b-dpo-qlora
results: []
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: 0.5031
- Rewards/chosen: -1.9728
- Rewards/rejected: -2.9618
- Rewards/accuracies: 0.7695
- Rewards/margins: 0.9890
- Logps/rejected: -543.7128
- Logps/chosen: -443.7073
- Logits/rejected: -1.1810
- Logits/chosen: -1.2525
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: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 64
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.5646 | 0.2093 | 100 | 0.5739 | -0.9253 | -1.4816 | 0.7188 | 0.5564 | -395.6964 | -338.9565 | -1.9267 | -1.9878 |
| 0.5524 | 0.4186 | 200 | 0.5318 | -0.8476 | -1.5395 | 0.7617 | 0.6919 | -401.4810 | -331.1845 | -1.5104 | -1.5801 |
| 0.4977 | 0.6279 | 300 | 0.5100 | -1.8821 | -2.8383 | 0.7773 | 0.9562 | -531.3586 | -434.6388 | -1.1156 | -1.1878 |
| 0.5096 | 0.8373 | 400 | 0.5035 | -2.0213 | -3.0170 | 0.7656 | 0.9957 | -549.2363 | -448.5603 | -1.1850 | -1.2569 |
Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.1.2+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1