---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: mistral-7b-dpo-full-wo-kqa_silver_wogold-ep3
  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. -->

# mistral-7b-dpo-full-wo-kqa_silver_wogold-ep3

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Logits/chosen: -3.2790
- Logits/rejected: -3.1123
- Logps/chosen: -721.5319
- Logps/rejected: -1477.7874
- Loss: 0.3206
- Rewards/accuracies: 0.8707
- Rewards/chosen: -1.9160
- Rewards/margins: 3.5495
- Rewards/rejected: -5.4655

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- 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 | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected |
|:-------------:|:-----:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:|
| 0.1362        | 0.65  | 100  | -3.2790       | -3.1123         | -721.5319    | -1477.7874     | 0.3206          | 0.8707             | -1.9160        | 3.5495          | -5.4655          |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2