---
license: apache-2.0
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
base_model: mistralai/Mistral-7B-Instruct-v0.2
datasets:
- nthakur/multilingual-ultrafeedback-binarized-dpo-v0.1
- nthakur/multilingual-distilabel-intel-orca-dpo-pairs-v0.1
- nthakur/multilingual-truthy-dpo-pairs-v0.1
- nthakur/GSM8KInstruct-Parallel-instruct-dpo-v0.1
model-index:
- name: Mistral-7B-Instruct-v0.2-multilingual-dpo-v1.0-v2
  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-Instruct-v0.2-multilingual-dpo-v1.0-v2

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the nthakur/multilingual-ultrafeedback-binarized-dpo-v0.1, the nthakur/multilingual-distilabel-intel-orca-dpo-pairs-v0.1, the nthakur/multilingual-truthy-dpo-pairs-v0.1 and the nthakur/GSM8KInstruct-Parallel-instruct-dpo-v0.1 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.1324
- Rewards/chosen: -2.6738
- Rewards/rejected: -12.2394
- Rewards/accuracies: 0.9377
- Rewards/margins: 9.5656
- Logps/rejected: -1515.8665
- Logps/chosen: -607.0774
- Logits/rejected: 0.4952
- Logits/chosen: 0.3030

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 2
- total_train_batch_size: 24
- total_eval_batch_size: 12
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.2695        | 0.1361 | 500  | 0.2653          | -0.4399        | -4.5379          | 0.8680             | 4.0981          | -745.7153      | -383.6803    | -1.3998         | -1.5327       |
| 0.4349        | 0.2723 | 1000 | 0.3152          | -2.6018        | -7.1212          | 0.8515             | 4.5195          | -1004.0471     | -599.8698    | 4.1724          | 4.7868        |
| 0.531         | 0.4084 | 1500 | 0.4873          | -2.4253        | -8.0681          | 0.7855             | 5.6428          | -1098.7278     | -582.2241    | -1.5195         | -1.6538       |
| 0.1681        | 0.5446 | 2000 | 0.2003          | -3.9555        | -13.1169         | 0.9089             | 9.1613          | -1603.6106     | -735.2488    | -0.1888         | -0.3742       |
| 0.1778        | 0.6807 | 2500 | 0.2004          | -3.4745        | -11.9768         | 0.9242             | 8.5023          | -1489.6012     | -687.1464    | -0.7118         | -0.9608       |
| 0.1342        | 0.8169 | 3000 | 0.1452          | -3.0928        | -12.8477         | 0.9340             | 9.7549          | -1576.6960     | -648.9738    | 0.6727          | 0.5428        |
| 0.1252        | 0.9530 | 3500 | 0.1328          | -2.7014        | -12.3976         | 0.9383             | 9.6962          | -1531.6849     | -609.8344    | 0.5002          | 0.3026        |


### Framework versions

- PEFT 0.7.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1