---
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_new_step10_0_80
  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_new_step10_0_80

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_new_step10_0_80 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5250
- Rewards/chosen: 0.5658
- Rewards/rejected: -2.2697
- Rewards/accuracies: 0.8307
- Rewards/margins: 2.8355
- Logps/rejected: -237.9764
- Logps/chosen: -250.5795
- Logits/rejected: -2.1447
- Logits/chosen: -2.1680

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.572         | 0.4673 | 50   | 0.5720          | 1.0708         | -0.2185          | 0.7578             | 1.2893          | -217.4643      | -245.5292    | -2.5291         | -2.5309       |
| 0.4997        | 0.9346 | 100  | 0.5102          | 0.8653         | -0.9135          | 0.7865             | 1.7788          | -224.4143      | -247.5850    | -2.1776         | -2.2008       |
| 0.2873        | 1.4019 | 150  | 0.5675          | 1.0559         | -1.2279          | 0.7891             | 2.2838          | -227.5579      | -245.6786    | -2.2632         | -2.2750       |
| 0.2853        | 1.8692 | 200  | 0.5163          | 0.7188         | -1.7114          | 0.8203             | 2.4302          | -232.3931      | -249.0491    | -2.1251         | -2.1478       |
| 0.1541        | 2.3364 | 250  | 0.5271          | 0.5977         | -2.1434          | 0.8177             | 2.7411          | -236.7135      | -250.2604    | -2.2153         | -2.2352       |
| 0.1566        | 2.8037 | 300  | 0.5242          | 0.5568         | -2.2821          | 0.8307             | 2.8389          | -238.1007      | -250.6694    | -2.1442         | -2.1674       |


### Framework versions

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