---
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: RLAIF-V-Coccur-q0_25_preference
  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. -->

# RLAIF-V-Coccur-q0_25_preference

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 RLAIF-V-Coccur-q0_25_preference dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5440
- Rewards/chosen: -2.3911
- Rewards/rejected: -4.1460
- Rewards/accuracies: 0.7188
- Rewards/margins: 1.7550
- Logps/rejected: -201.5194
- Logps/chosen: -183.7933
- Logits/rejected: -2.7049
- Logits/chosen: -2.7311

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5904        | 0.6944 | 50   | 0.5585          | 0.1767         | -0.5308          | 0.6953             | 0.7075          | -165.3675      | -158.1156    | -2.7400         | -2.7505       |
| 0.2124        | 1.3889 | 100  | 0.5330          | -0.9785        | -2.2414          | 0.7344             | 1.2630          | -182.4733      | -169.6674    | -2.6846         | -2.7028       |
| 0.1027        | 2.0833 | 150  | 0.5209          | -1.3289        | -2.7382          | 0.7305             | 1.4093          | -187.4415      | -173.1719    | -2.7648         | -2.7841       |
| 0.0793        | 2.7778 | 200  | 0.5435          | -2.3758        | -4.1313          | 0.7227             | 1.7554          | -201.3717      | -183.6412    | -2.7055         | -2.7316       |


### Framework versions

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