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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_70
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_70
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_70 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5414
- Rewards/chosen: 0.5872
- Rewards/rejected: -1.5508
- Rewards/accuracies: 0.7768
- Rewards/margins: 2.1380
- Logps/rejected: -227.1739
- Logps/chosen: -233.6734
- Logits/rejected: -1.9224
- Logits/chosen: -1.9691
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6034 | 0.5348 | 50 | 0.5869 | 0.7400 | -0.1413 | 0.7292 | 0.8813 | -213.0786 | -232.1449 | -2.5305 | -2.5372 |
| 0.2659 | 1.0695 | 100 | 0.5500 | 1.0886 | -0.4196 | 0.7679 | 1.5081 | -215.8615 | -228.6596 | -2.1146 | -2.1482 |
| 0.2599 | 1.6043 | 150 | 0.5465 | 0.7596 | -1.0841 | 0.7679 | 1.8437 | -222.5069 | -231.9491 | -2.1122 | -2.1442 |
| 0.1366 | 2.1390 | 200 | 0.5222 | 0.5890 | -1.4225 | 0.7857 | 2.0115 | -225.8904 | -233.6554 | -2.0824 | -2.1154 |
| 0.1488 | 2.6738 | 250 | 0.5411 | 0.5980 | -1.5260 | 0.7768 | 2.1240 | -226.9253 | -233.5653 | -1.9322 | -1.9781 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.3
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