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---
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_80
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_80
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_80 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5250
- Rewards/chosen: 0.5658
- Rewards/rejected: -2.2697
- Rewards/accuracies: 0.8307
- Rewards/margins: 2.8355
- Logps/rejected: -237.9764
- Logps/chosen: -250.5795
- Logits/rejected: -2.1447
- Logits/chosen: -2.1680
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.572 | 0.4673 | 50 | 0.5720 | 1.0708 | -0.2185 | 0.7578 | 1.2893 | -217.4643 | -245.5292 | -2.5291 | -2.5309 |
| 0.4997 | 0.9346 | 100 | 0.5102 | 0.8653 | -0.9135 | 0.7865 | 1.7788 | -224.4143 | -247.5850 | -2.1776 | -2.2008 |
| 0.2873 | 1.4019 | 150 | 0.5675 | 1.0559 | -1.2279 | 0.7891 | 2.2838 | -227.5579 | -245.6786 | -2.2632 | -2.2750 |
| 0.2853 | 1.8692 | 200 | 0.5163 | 0.7188 | -1.7114 | 0.8203 | 2.4302 | -232.3931 | -249.0491 | -2.1251 | -2.1478 |
| 0.1541 | 2.3364 | 250 | 0.5271 | 0.5977 | -2.1434 | 0.8177 | 2.7411 | -236.7135 | -250.2604 | -2.2153 | -2.2352 |
| 0.1566 | 2.8037 | 300 | 0.5242 | 0.5568 | -2.2821 | 0.8307 | 2.8389 | -238.1007 | -250.6694 | -2.1442 | -2.1674 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.3
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