---
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_l0_new_step10_0_70
  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_l0_new_step10_0_70

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_l0_new_step10_0_70 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5015
- Rewards/chosen: 0.2932
- Rewards/rejected: -2.5932
- Rewards/accuracies: 0.8274
- Rewards/margins: 2.8864
- Logps/rejected: -244.7975
- Logps/chosen: -248.1062
- Logits/rejected: -2.1491
- Logits/chosen: -2.2057

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5372        | 0.5348 | 50   | 0.5589          | 0.8885         | -0.7687          | 0.7708             | 1.6573          | -226.5533      | -242.1535    | -2.5558         | -2.5652       |
| 0.2535        | 1.0695 | 100  | 0.5072          | 0.6618         | -1.4593          | 0.8155             | 2.1211          | -233.4590      | -244.4205    | -2.3160         | -2.3489       |
| 0.2927        | 1.6043 | 150  | 0.5305          | 0.2199         | -2.4527          | 0.8065             | 2.6726          | -243.3929      | -248.8394    | -2.2493         | -2.2896       |
| 0.1722        | 2.1390 | 200  | 0.4972          | 0.5435         | -2.1567          | 0.8304             | 2.7003          | -240.4332      | -245.6031    | -2.1267         | -2.1841       |
| 0.1412        | 2.6738 | 250  | 0.5014          | 0.2961         | -2.5802          | 0.8214             | 2.8763          | -244.6681      | -248.0778    | -2.1488         | -2.2053       |


### Framework versions

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