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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: RLAIF-V-Cosi-q0_25_preference
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. -->
# RLAIF-V-Cosi-q0_25_preference
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 RLAIF-V-Cosi-q0_25_preference dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5909
- Rewards/chosen: -2.7988
- Rewards/rejected: -4.2628
- Rewards/accuracies: 0.7266
- Rewards/margins: 1.4639
- Logps/rejected: -211.2034
- Logps/chosen: -194.0678
- Logits/rejected: -2.6060
- Logits/chosen: -2.6047
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.575 | 0.6944 | 50 | 0.5680 | -0.5232 | -1.1499 | 0.6914 | 0.6267 | -180.0744 | -171.3114 | -2.7966 | -2.7982 |
| 0.2161 | 1.3889 | 100 | 0.5416 | -1.1269 | -2.2892 | 0.7461 | 1.1623 | -191.4681 | -177.3486 | -2.6708 | -2.6714 |
| 0.0912 | 2.0833 | 150 | 0.5559 | -2.1342 | -3.5698 | 0.7188 | 1.4356 | -204.2739 | -187.4216 | -2.6701 | -2.6674 |
| 0.0828 | 2.7778 | 200 | 0.5902 | -2.7717 | -4.2295 | 0.7227 | 1.4578 | -210.8705 | -193.7959 | -2.6071 | -2.6057 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.3
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