---
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_cocour_new_step10_0_30
  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_cocour_new_step10_0_30

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_cocour_new_step10_0_30 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5532
- Rewards/chosen: 1.6544
- Rewards/rejected: -1.2534
- Rewards/accuracies: 0.8056
- Rewards/margins: 2.9078
- Logps/rejected: -252.7311
- Logps/chosen: -241.2080
- Logits/rejected: -2.0966
- Logits/chosen: -2.1262

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.2648        | 1.2422 | 50   | 0.5693          | 2.0296         | -0.4936          | 0.8125             | 2.5232          | -245.1335      | -237.4563    | -2.3209         | -2.3384       |
| 0.1487        | 2.4845 | 100  | 0.5524          | 1.6519         | -1.2519          | 0.8125             | 2.9039          | -252.7170      | -241.2330    | -2.0940         | -2.1241       |


### Framework versions

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