---
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_text_image_to_text
  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_text_image_to_text

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_text_image_to_text dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4500
- Rewards/chosen: -0.6971
- Rewards/rejected: -4.4006
- Rewards/accuracies: 0.8206
- Rewards/margins: 3.7035
- Logps/rejected: -242.2139
- Logps/chosen: -207.2900
- Logits/rejected: -1.9132
- Logits/chosen: -1.9735

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.4516        | 0.3623 | 50   | 0.4421          | 0.8113         | -0.8305          | 0.7903             | 1.6418          | -206.5130      | -192.2066    | -1.6310         | -1.7066       |
| 0.3759        | 0.7246 | 100  | 0.4121          | -0.0472        | -2.2762          | 0.8145             | 2.2290          | -220.9696      | -200.7911    | -1.7930         | -1.8524       |
| 0.149         | 1.0870 | 150  | 0.4205          | 0.5835         | -1.8816          | 0.8206             | 2.4651          | -217.0244      | -194.4847    | -1.6746         | -1.7425       |
| 0.1474        | 1.4493 | 200  | 0.4274          | -0.5411        | -3.7374          | 0.8306             | 3.1963          | -235.5818      | -205.7306    | -1.7947         | -1.8599       |
| 0.1268        | 1.8116 | 250  | 0.4333          | -0.0670        | -3.3107          | 0.8206             | 3.2437          | -231.3154      | -200.9896    | -2.0993         | -2.1450       |
| 0.064         | 2.1739 | 300  | 0.4332          | -0.5167        | -4.0958          | 0.8306             | 3.5792          | -239.1665      | -205.4860    | -1.9327         | -1.9909       |
| 0.056         | 2.5362 | 350  | 0.4481          | -0.5224        | -4.1134          | 0.8185             | 3.5910          | -239.3422      | -205.5439    | -1.9163         | -1.9756       |
| 0.0721        | 2.8986 | 400  | 0.4507          | -0.7023        | -4.4082          | 0.8185             | 3.7059          | -242.2901      | -207.3426    | -1.9129         | -1.9731       |


### Framework versions

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