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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_new_step10_0_100
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_new_step10_0_100
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_new_step10_0_100 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4957
- Rewards/chosen: -0.4320
- Rewards/rejected: -3.0552
- Rewards/accuracies: 0.7917
- Rewards/margins: 2.6232
- Logps/rejected: -248.9210
- Logps/chosen: -252.8571
- Logits/rejected: -2.2740
- Logits/chosen: -2.3049
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.577 | 0.3738 | 50 | 0.5782 | 0.7960 | -0.1800 | 0.7250 | 0.9759 | -220.1687 | -240.5771 | -2.1546 | -2.1689 |
| 0.5388 | 0.7477 | 100 | 0.5391 | -0.4398 | -2.0133 | 0.7479 | 1.5735 | -238.5014 | -252.9343 | -2.1740 | -2.1991 |
| 0.2653 | 1.1215 | 150 | 0.5247 | 0.2862 | -1.6846 | 0.7646 | 1.9708 | -235.2147 | -245.6745 | -2.3266 | -2.3485 |
| 0.2571 | 1.4953 | 200 | 0.5108 | -0.5979 | -3.0808 | 0.7792 | 2.4828 | -249.1766 | -254.5160 | -2.4752 | -2.5016 |
| 0.2803 | 1.8692 | 250 | 0.4817 | -0.2909 | -2.6866 | 0.7854 | 2.3957 | -245.2348 | -251.4460 | -2.3853 | -2.4107 |
| 0.1739 | 2.2430 | 300 | 0.4912 | -0.3815 | -2.8477 | 0.7917 | 2.4662 | -246.8459 | -252.3520 | -2.3281 | -2.3560 |
| 0.1631 | 2.6168 | 350 | 0.4965 | -0.4101 | -3.0083 | 0.7896 | 2.5982 | -248.4518 | -252.6378 | -2.2784 | -2.3092 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.3
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