---
library_name: transformers
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.2
tags:
- alignment-handbook
- trl
- simpo
- generated_from_trainer
- trl
- simpo
- generated_from_trainer
datasets:
- princeton-nlp/mistral-instruct-ultrafeedback
model-index:
- name: mistral-7b-instruct-v0.2-rsimpo-full
  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-rsimpo-full

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 princeton-nlp/mistral-instruct-ultrafeedback dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7976
- Rewards/chosen: -1.2291
- Rewards/rejected: -1.3244
- Rewards/accuracies: 0.5507
- Rewards/margins: 0.0955
- Agreement Weights/mean: 0.9696
- Agreement Weights/std: 0.0182
- Eta/annotator 0: 0.9730

## 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-07
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 16
- total_train_batch_size: 256
- total_eval_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results



### Framework versions

- Transformers 4.46.3
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.20.3