---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- 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 [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5270
- Rewards/chosen: -0.1210
- Rewards/rejected: -0.9978
- Rewards/accuracies: 0.7812
- Rewards/margins: 0.8768
- Logps/rejected: -198.5849
- Logps/chosen: -248.6519
- Logits/rejected: -1.9190
- Logits/chosen: -2.0860

## 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: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 32
- total_train_batch_size: 64
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5491        | 1.0   | 969  | 0.5563          | -0.0962        | -0.7226          | 0.7812             | 0.6263          | -195.8333      | -248.4046    | -1.9755         | -2.1375       |
| 0.5454        | 2.0   | 1938 | 0.5312          | -0.1249        | -0.9600          | 0.7969             | 0.8351          | -198.2077      | -248.6910    | -1.9316         | -2.0971       |
| 0.5242        | 3.0   | 2907 | 0.5270          | -0.1210        | -0.9978          | 0.7812             | 0.8768          | -198.5849      | -248.6519    | -1.9190         | -2.0860       |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1