---
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_random_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_random_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_random_0_80 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5567
- Rewards/chosen: -0.0039
- Rewards/rejected: -2.3714
- Rewards/accuracies: 0.8021
- Rewards/margins: 2.3675
- Logps/rejected: -234.5394
- Logps/chosen: -232.6765
- Logits/rejected: -2.2685
- Logits/chosen: -2.3031

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.576         | 0.4673 | 50   | 0.5725          | 0.8730         | -0.1201          | 0.7318             | 0.9931          | -212.0256      | -223.9073    | -2.4706         | -2.4964       |
| 0.508         | 0.9346 | 100  | 0.5507          | -0.2081        | -1.7933          | 0.7865             | 1.5852          | -228.7584      | -234.7186    | -2.4439         | -2.4604       |
| 0.2512        | 1.4019 | 150  | 0.5608          | 0.2020         | -1.8022          | 0.7865             | 2.0042          | -228.8469      | -230.6172    | -2.2977         | -2.3324       |
| 0.3125        | 1.8692 | 200  | 0.5447          | 0.4722         | -1.5712          | 0.8099             | 2.0434          | -226.5372      | -227.9149    | -2.2994         | -2.3304       |
| 0.1519        | 2.3364 | 250  | 0.5571          | 0.1894         | -2.0352          | 0.8047             | 2.2246          | -231.1766      | -230.7427    | -2.3302         | -2.3582       |
| 0.1708        | 2.8037 | 300  | 0.5571          | 0.0000         | -2.3612          | 0.8073             | 2.3612          | -234.4372      | -232.6371    | -2.2672         | -2.3019       |


### Framework versions

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