---
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_Cherry_0_60
  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_Cherry_0_60

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_Cherry_0_60 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4983
- Rewards/chosen: 2.3376
- Rewards/rejected: -0.8230
- Rewards/accuracies: 0.8074
- Rewards/margins: 3.1606
- Logps/rejected: -240.8466
- Logps/chosen: -306.5101
- Logits/rejected: -2.0946
- Logits/chosen: -2.1213

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5436        | 0.4923 | 40   | 0.5011          | 2.5953         | 0.9447           | 0.7736             | 1.6506          | -223.1691      | -303.9334    | -2.0088         | -2.0351       |
| 0.4689        | 0.9846 | 80   | 0.4769          | 1.8328         | -0.2925          | 0.8074             | 2.1253          | -235.5412      | -311.5584    | -2.2292         | -2.2518       |
| 0.1825        | 1.4769 | 120  | 0.5121          | 1.9848         | -0.7992          | 0.8142             | 2.7840          | -240.6085      | -310.0383    | -2.1958         | -2.2158       |
| 0.2112        | 1.9692 | 160  | 0.4885          | 2.4604         | -0.3263          | 0.8176             | 2.7867          | -235.8799      | -305.2829    | -2.1603         | -2.1813       |
| 0.1059        | 2.4615 | 200  | 0.4947          | 2.3506         | -0.7274          | 0.8108             | 3.0780          | -239.8905      | -306.3801    | -2.1061         | -2.1317       |
| 0.1134        | 2.9538 | 240  | 0.4985          | 2.3366         | -0.8241          | 0.8108             | 3.1607          | -240.8571      | -306.5204    | -2.0945         | -2.1211       |


### Framework versions

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