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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_random_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_random_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_random_0_80 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5567
- Rewards/chosen: -0.0039
- Rewards/rejected: -2.3714
- Rewards/accuracies: 0.8021
- Rewards/margins: 2.3675
- Logps/rejected: -234.5394
- Logps/chosen: -232.6765
- Logits/rejected: -2.2685
- Logits/chosen: -2.3031
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.576 | 0.4673 | 50 | 0.5725 | 0.8730 | -0.1201 | 0.7318 | 0.9931 | -212.0256 | -223.9073 | -2.4706 | -2.4964 |
| 0.508 | 0.9346 | 100 | 0.5507 | -0.2081 | -1.7933 | 0.7865 | 1.5852 | -228.7584 | -234.7186 | -2.4439 | -2.4604 |
| 0.2512 | 1.4019 | 150 | 0.5608 | 0.2020 | -1.8022 | 0.7865 | 2.0042 | -228.8469 | -230.6172 | -2.2977 | -2.3324 |
| 0.3125 | 1.8692 | 200 | 0.5447 | 0.4722 | -1.5712 | 0.8099 | 2.0434 | -226.5372 | -227.9149 | -2.2994 | -2.3304 |
| 0.1519 | 2.3364 | 250 | 0.5571 | 0.1894 | -2.0352 | 0.8047 | 2.2246 | -231.1766 | -230.7427 | -2.3302 | -2.3582 |
| 0.1708 | 2.8037 | 300 | 0.5571 | 0.0000 | -2.3612 | 0.8073 | 2.3612 | -234.4372 | -232.6371 | -2.2672 | -2.3019 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.3
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