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---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# zephyr-7b-dpo-qlora

This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-qlora](https://huggingface.co/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