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---
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
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-ORPO
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 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8975
- Rewards/chosen: -0.0835
- Rewards/rejected: -0.1074
- Rewards/accuracies: 0.5900
- Rewards/margins: 0.0238
- Logps/rejected: -1.0737
- Logps/chosen: -0.8352
- Logits/rejected: -2.8721
- Logits/chosen: -2.8461
- Sft Loss: 0.8352
- Odds Ratio Loss: 0.6231
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:---------------:|
| 1.0001 | 0.8891 | 500 | 0.9318 | -0.0869 | -0.1112 | 0.5920 | 0.0243 | -1.1123 | -0.8690 | -2.8936 | -2.8713 | 0.8690 | 0.6284 |
| 0.906 | 1.7782 | 1000 | 0.9039 | -0.0841 | -0.1081 | 0.5780 | 0.0240 | -1.0811 | -0.8415 | -2.8783 | -2.8533 | 0.8415 | 0.6243 |
| 0.9019 | 2.6673 | 1500 | 0.8975 | -0.0835 | -0.1074 | 0.5900 | 0.0238 | -1.0737 | -0.8352 | -2.8721 | -2.8461 | 0.8352 | 0.6231 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1 |