---
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_90
  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_90

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_90 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5266
- Rewards/chosen: 0.6411
- Rewards/rejected: -1.9030
- Rewards/accuracies: 0.7986
- Rewards/margins: 2.5441
- Logps/rejected: -230.4333
- Logps/chosen: -239.3183
- Logits/rejected: -2.0706
- Logits/chosen: -2.1025

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.635         | 0.4158 | 50   | 0.5987          | 0.8451         | -0.0388          | 0.7014             | 0.8840          | -211.7915      | -237.2780    | -2.3908         | -2.3899       |
| 0.4933        | 0.8316 | 100  | 0.5285          | -0.2263        | -1.8151          | 0.7523             | 1.5888          | -229.5545      | -247.9923    | -1.9128         | -1.9530       |
| 0.2495        | 1.2474 | 150  | 0.5427          | 0.5572         | -1.4201          | 0.7593             | 1.9773          | -225.6041      | -240.1570    | -2.0983         | -2.1232       |
| 0.2753        | 1.6632 | 200  | 0.5260          | 0.5776         | -1.6735          | 0.7870             | 2.2511          | -228.1382      | -239.9529    | -1.9752         | -2.0068       |
| 0.1584        | 2.0790 | 250  | 0.5118          | 0.5255         | -1.9057          | 0.7940             | 2.4312          | -230.4605      | -240.4746    | -2.0354         | -2.0689       |
| 0.1572        | 2.4948 | 300  | 0.5261          | 0.7582         | -1.7260          | 0.7986             | 2.4842          | -228.6629      | -238.1469    | -2.0616         | -2.0941       |
| 0.1557        | 2.9106 | 350  | 0.5265          | 0.6414         | -1.9061          | 0.7986             | 2.5475          | -230.4645      | -239.3154    | -2.0706         | -2.1026       |


### Framework versions

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