---
license: apache-2.0
library_name: peft
tags:
- llama-factory
- lora
- trl
- dpo
- generated_from_trainer
base_model: mistralai/Mistral-7B-Instruct-v0.3
model-index:
- name: Mistral-7B-Instruct-v0.3-ORPO-SALT-HALF
  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-v0.3-ORPO-SALT-HALF

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on the dpo_mix_en and the bct_non_cot_dpo_500 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.8506
- Rewards/chosen: -0.0787
- Rewards/rejected: -0.0996
- Rewards/accuracies: 0.5724
- Rewards/margins: 0.0209
- Logps/rejected: -0.9956
- Logps/chosen: -0.7867
- Logits/rejected: -3.1507
- Logits/chosen: -3.1305
- Sft Loss: 0.7867
- Odds Ratio Loss: 0.6382

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 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 | Sft Loss | Odds Ratio Loss |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:---------------:|
| 0.8758        | 0.8467 | 500  | 0.8691          | -0.0805        | -0.1009          | 0.5705             | 0.0203          | -1.0086        | -0.8054      | -3.1276         | -3.1089       | 0.8054   | 0.6371          |
| 0.8098        | 1.6935 | 1000 | 0.8549          | -0.0791        | -0.0999          | 0.5676             | 0.0207          | -0.9985        | -0.7911      | -3.1170         | -3.0966       | 0.7911   | 0.6375          |
| 0.8135        | 2.5402 | 1500 | 0.8506          | -0.0787        | -0.0996          | 0.5724             | 0.0209          | -0.9956        | -0.7867      | -3.1507         | -3.1305       | 0.7867   | 0.6382          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1