---
base_model: HuggingFaceH4/mistral-7b-sft-beta
library_name: peft
license: mit
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
model-index:
- name: zephyr-7b-dpo-lora
  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-lora

This model is a fine-tuned version of [HuggingFaceH4/mistral-7b-sft-beta](https://huggingface.co/HuggingFaceH4/mistral-7b-sft-beta) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5082
- Rewards/chosen: 0.0025
- Rewards/rejected: -0.9047
- Rewards/accuracies: 0.7222
- Rewards/margins: 0.9072
- Logps/rejected: -276.6852
- Logps/chosen: -271.8461
- Logits/rejected: -2.7167
- Logits/chosen: -2.7365

## 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: 4
- gradient_accumulation_steps: 4
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5795        | 0.1047 | 100  | 0.5875          | 0.0265         | -0.3721          | 0.6825             | 0.3986          | -271.3593      | -271.6063    | -2.7688         | -2.7900       |
| 0.5449        | 0.2094 | 200  | 0.5520          | 0.0601         | -0.5726          | 0.7103             | 0.6327          | -273.3645      | -271.2704    | -2.7792         | -2.7981       |
| 0.545         | 0.3141 | 300  | 0.5320          | -0.0197        | -0.7637          | 0.7044             | 0.7439          | -275.2751      | -272.0686    | -2.7616         | -2.7803       |
| 0.4747        | 0.4187 | 400  | 0.5228          | -0.1728        | -0.9527          | 0.7004             | 0.7798          | -277.1651      | -273.5996    | -2.7532         | -2.7732       |
| 0.5367        | 0.5234 | 500  | 0.5175          | -0.2142        | -1.0435          | 0.7143             | 0.8293          | -278.0737      | -274.0135    | -2.7339         | -2.7540       |
| 0.5031        | 0.6281 | 600  | 0.5139          | -0.2939        | -1.1329          | 0.7024             | 0.8389          | -278.9670      | -274.8105    | -2.7071         | -2.7268       |
| 0.5057        | 0.7328 | 700  | 0.5084          | -0.0108        | -0.9049          | 0.7202             | 0.8941          | -276.6876      | -271.9794    | -2.7207         | -2.7404       |
| 0.5172        | 0.8375 | 800  | 0.5090          | -0.0300        | -0.9231          | 0.7183             | 0.8931          | -276.8697      | -272.1711    | -2.7173         | -2.7371       |
| 0.5173        | 0.9422 | 900  | 0.5084          | -0.0008        | -0.9080          | 0.7222             | 0.9072          | -276.7181      | -271.8789    | -2.7174         | -2.7372       |


### Framework versions

- PEFT 0.7.1
- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.14.6
- Tokenizers 0.20.1