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

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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8434
- Rewards/chosen: -0.0777
- Rewards/rejected: -0.0988
- Rewards/accuracies: 0.5691
- Rewards/margins: 0.0210
- Logps/rejected: -0.9877
- Logps/chosen: -0.7773
- Logits/rejected: -3.1073
- Logits/chosen: -3.0834
- Sft Loss: 0.7773
- Odds Ratio Loss: 0.6614

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:---------------:|
| 0.8803        | 0.8082 | 500  | 0.8619          | -0.0796        | -0.0983          | 0.5655             | 0.0187          | -0.9834        | -0.7962      | -3.0746         | -3.0520       | 0.7962   | 0.6572          |
| 0.7341        | 1.6165 | 1000 | 0.8450          | -0.0779        | -0.0980          | 0.5673             | 0.0201          | -0.9804        | -0.7795      | -3.1194         | -3.0960       | 0.7795   | 0.6550          |
| 0.7691        | 2.4247 | 1500 | 0.8434          | -0.0777        | -0.0988          | 0.5691             | 0.0210          | -0.9877        | -0.7773      | -3.1073         | -3.0834       | 0.7773   | 0.6614          |


### Framework versions

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