---
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: 0.4527
- Rewards/chosen: -0.6857
- Rewards/rejected: -4.3940
- Rewards/accuracies: 0.8165
- Rewards/margins: 3.7083
- Logps/rejected: -242.1480
- Logps/chosen: -207.1762
- Logits/rejected: -2.3240
- Logits/chosen: -2.3485

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.4889        | 0.2899 | 40   | 0.4642          | 1.1544         | -0.1887          | 0.7944             | 1.3431          | -200.0950      | -188.7752    | -1.9876         | -2.0351       |
| 0.3941        | 0.5797 | 80   | 0.4218          | -0.2275        | -2.2919          | 0.8044             | 2.0644          | -221.1273      | -202.5944    | -1.9449         | -1.9901       |
| 0.3717        | 0.8696 | 120  | 0.4387          | -0.2101        | -2.4885          | 0.8286             | 2.2784          | -223.0936      | -202.4208    | -2.0902         | -2.1229       |
| 0.1459        | 1.1594 | 160  | 0.4288          | -0.4029        | -3.3928          | 0.8286             | 2.9899          | -232.1363      | -204.3488    | -2.2733         | -2.3007       |
| 0.1455        | 1.4493 | 200  | 0.4255          | -0.5338        | -3.6331          | 0.8165             | 3.0992          | -234.5387      | -205.6577    | -2.2466         | -2.2697       |
| 0.1358        | 1.7391 | 240  | 0.4247          | -0.2714        | -3.6715          | 0.8327             | 3.4001          | -234.9227      | -203.0333    | -2.3605         | -2.3806       |
| 0.0938        | 2.0290 | 280  | 0.4128          | -0.3136        | -3.7007          | 0.8266             | 3.3870          | -235.2147      | -203.4556    | -2.3725         | -2.3933       |
| 0.0592        | 2.3188 | 320  | 0.4438          | -0.5767        | -4.1235          | 0.8165             | 3.5467          | -239.4429      | -206.0869    | -2.3109         | -2.3358       |
| 0.0673        | 2.6087 | 360  | 0.4553          | -0.6264        | -4.3005          | 0.8206             | 3.6740          | -241.2126      | -206.5837    | -2.3254         | -2.3497       |
| 0.0728        | 2.8986 | 400  | 0.4520          | -0.6855        | -4.3942          | 0.8185             | 3.7087          | -242.1503      | -207.1744    | -2.3247         | -2.3492       |


### Framework versions

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