---
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_cosi_0_75
  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_cosi_0_75

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_cosi_0_75 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5439
- Rewards/chosen: 1.0617
- Rewards/rejected: -1.0230
- Rewards/accuracies: 0.7292
- Rewards/margins: 2.0847
- Logps/rejected: -221.4094
- Logps/chosen: -257.3853
- Logits/rejected: -2.2898
- Logits/chosen: -2.2986

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5811        | 0.7463 | 50   | 0.5699          | 0.5697         | -0.6122          | 0.7333             | 1.1819          | -217.3008      | -262.3048    | -2.3887         | -2.3796       |
| 0.2898        | 1.4925 | 100  | 0.5633          | 1.2446         | -0.5551          | 0.7583             | 1.7998          | -216.7303      | -255.5556    | -2.4747         | -2.4717       |
| 0.131         | 2.2388 | 150  | 0.5345          | 1.2941         | -0.7142          | 0.7625             | 2.0083          | -218.3207      | -255.0607    | -2.3181         | -2.3241       |
| 0.1357        | 2.9851 | 200  | 0.5440          | 1.0620         | -1.0267          | 0.7333             | 2.0886          | -221.4456      | -257.3822    | -2.2899         | -2.2988       |


### Framework versions

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