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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_Cherry_0_90
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_Cherry_0_90
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_Cherry_0_90 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5233
- Rewards/chosen: 0.7968
- Rewards/rejected: -1.8577
- Rewards/accuracies: 0.8218
- Rewards/margins: 2.6545
- Logps/rejected: -234.1042
- Logps/chosen: -250.9109
- Logits/rejected: -1.8912
- Logits/chosen: -1.9506
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.4674 | 0.8230 | 100 | 0.4985 | 0.1779 | -1.6218 | 0.7940 | 1.7997 | -231.7454 | -257.0998 | -2.2566 | -2.2803 |
| 0.2463 | 1.6461 | 200 | 0.5190 | 1.1459 | -1.2068 | 0.7963 | 2.3527 | -227.5959 | -247.4204 | -1.6292 | -1.7063 |
| 0.1311 | 2.4691 | 300 | 0.5212 | 0.6944 | -1.9013 | 0.8194 | 2.5958 | -234.5411 | -251.9348 | -1.8631 | -1.9243 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.3
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