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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_60
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_60
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_60 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4983
- Rewards/chosen: 2.3376
- Rewards/rejected: -0.8230
- Rewards/accuracies: 0.8074
- Rewards/margins: 3.1606
- Logps/rejected: -240.8466
- Logps/chosen: -306.5101
- Logits/rejected: -2.0946
- Logits/chosen: -2.1213
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5436 | 0.4923 | 40 | 0.5011 | 2.5953 | 0.9447 | 0.7736 | 1.6506 | -223.1691 | -303.9334 | -2.0088 | -2.0351 |
| 0.4689 | 0.9846 | 80 | 0.4769 | 1.8328 | -0.2925 | 0.8074 | 2.1253 | -235.5412 | -311.5584 | -2.2292 | -2.2518 |
| 0.1825 | 1.4769 | 120 | 0.5121 | 1.9848 | -0.7992 | 0.8142 | 2.7840 | -240.6085 | -310.0383 | -2.1958 | -2.2158 |
| 0.2112 | 1.9692 | 160 | 0.4885 | 2.4604 | -0.3263 | 0.8176 | 2.7867 | -235.8799 | -305.2829 | -2.1603 | -2.1813 |
| 0.1059 | 2.4615 | 200 | 0.4947 | 2.3506 | -0.7274 | 0.8108 | 3.0780 | -239.8905 | -306.3801 | -2.1061 | -2.1317 |
| 0.1134 | 2.9538 | 240 | 0.4985 | 2.3366 | -0.8241 | 0.8108 | 3.1607 | -240.8571 | -306.5204 | -2.0945 | -2.1211 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.3
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