---
license: mit
base_model: HuggingFaceH4/mistral-7b-sft-beta
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 [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: 0.3553
- Rewards/chosen: -0.8622
- Rewards/rejected: -3.1235
- Rewards/accuracies: 0.8281
- Rewards/margins: 2.2613
- Logps/rejected: -204.2707
- Logps/chosen: -282.4587
- Logits/rejected: -2.6699
- Logits/chosen: -2.7156

## 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: 2e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 128
- 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: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.2024        | 1.0   | 485  | 0.4197          | -0.3974        | -1.8930          | 0.8086             | 1.4956          | -191.9660      | -277.8107    | -2.7272         | -2.7680       |
| 0.1305        | 2.0   | 970  | 0.3694          | -0.7584        | -2.8597          | 0.8242             | 2.1013          | -201.6330      | -281.4208    | -2.6866         | -2.7306       |
| 0.109         | 3.0   | 1455 | 0.3553          | -0.8622        | -3.1235          | 0.8281             | 2.2613          | -204.2707      | -282.4587    | -2.6699         | -2.7156       |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.1+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1