---
library_name: transformers
license: other
base_model: llava-hf/llava-v1.6-mistral-7b-hf
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: AA_preference_cocour_0_50
  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. -->

# AA_preference_cocour_0_50

This model is a fine-tuned version of [llava-hf/llava-v1.6-mistral-7b-hf](https://huggingface.co/llava-hf/llava-v1.6-mistral-7b-hf) on the AA_preference_cocour_0_50 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4988
- Rewards/chosen: 0.9568
- Rewards/rejected: -1.9780
- Rewards/accuracies: 0.8500
- Rewards/margins: 2.9348
- Logps/rejected: -217.8485
- Logps/chosen: -263.8239
- Logits/rejected: -2.1050
- Logits/chosen: -2.1590

## 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: 1e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6027        | 0.7463 | 50   | 0.5491          | 1.3803         | -0.2983          | 0.8208             | 1.6786          | -201.0510      | -259.5887    | -2.4356         | -2.4575       |
| 0.2795        | 1.4925 | 100  | 0.5112          | 1.1590         | -1.5093          | 0.8417             | 2.6683          | -213.1614      | -261.8016    | -1.9102         | -1.9756       |
| 0.1557        | 2.2388 | 150  | 0.5033          | 1.3754         | -1.3325          | 0.8583             | 2.7079          | -211.3931      | -259.6372    | -2.1170         | -2.1696       |
| 0.1338        | 2.9851 | 200  | 0.4983          | 0.9563         | -1.9762          | 0.8500             | 2.9325          | -217.8308      | -263.8291    | -2.1047         | -2.1588       |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.3