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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_0_50
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_0_50
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_0_50 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4988
- Rewards/chosen: 0.9568
- Rewards/rejected: -1.9780
- Rewards/accuracies: 0.8500
- Rewards/margins: 2.9348
- Logps/rejected: -217.8485
- Logps/chosen: -263.8239
- Logits/rejected: -2.1050
- Logits/chosen: -2.1590
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6027 | 0.7463 | 50 | 0.5491 | 1.3803 | -0.2983 | 0.8208 | 1.6786 | -201.0510 | -259.5887 | -2.4356 | -2.4575 |
| 0.2795 | 1.4925 | 100 | 0.5112 | 1.1590 | -1.5093 | 0.8417 | 2.6683 | -213.1614 | -261.8016 | -1.9102 | -1.9756 |
| 0.1557 | 2.2388 | 150 | 0.5033 | 1.3754 | -1.3325 | 0.8583 | 2.7079 | -211.3931 | -259.6372 | -2.1170 | -2.1696 |
| 0.1338 | 2.9851 | 200 | 0.4983 | 0.9563 | -1.9762 | 0.8500 | 2.9325 | -217.8308 | -263.8291 | -2.1047 | -2.1588 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.3
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