---
license: apache-2.0
library_name: peft
tags:
- llama-factory
- lora
- trl
- dpo
- generated_from_trainer
base_model: mistralai/Mistral-7B-Instruct-v0.2
model-index:
- name: Mistral-7B-Instruct-v0.2-ORPO-SALT
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Mistral-7B-Instruct-v0.2-ORPO-SALT

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 dpo_mix_en and the bct_non_cot_dpo_1000 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.8630
- Rewards/chosen: -0.0798
- Rewards/rejected: -0.1033
- Rewards/accuracies: 0.5618
- Rewards/margins: 0.0235
- Logps/rejected: -1.0328
- Logps/chosen: -0.7975
- Logits/rejected: -2.8558
- Logits/chosen: -2.8473
- Sft Loss: 0.7975
- Odds Ratio Loss: 0.6547

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:---------------:|
| 0.93          | 0.8082 | 500  | 0.8928          | -0.0828        | -0.1057          | 0.5773             | 0.0229          | -1.0567        | -0.8278      | -2.8442         | -2.8368       | 0.8278   | 0.6496          |
| 0.7571        | 1.6165 | 1000 | 0.8679          | -0.0803        | -0.1034          | 0.5700             | 0.0231          | -1.0337        | -0.8028      | -2.8729         | -2.8644       | 0.8028   | 0.6510          |
| 0.8035        | 2.4247 | 1500 | 0.8630          | -0.0798        | -0.1033          | 0.5618             | 0.0235          | -1.0328        | -0.7975      | -2.8558         | -2.8473       | 0.7975   | 0.6547          |


### Framework versions

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