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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_l0_new_step10_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_l0_new_step10_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_l0_new_step10_0_70 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5015
- Rewards/chosen: 0.2932
- Rewards/rejected: -2.5932
- Rewards/accuracies: 0.8274
- Rewards/margins: 2.8864
- Logps/rejected: -244.7975
- Logps/chosen: -248.1062
- Logits/rejected: -2.1491
- Logits/chosen: -2.2057
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5372 | 0.5348 | 50 | 0.5589 | 0.8885 | -0.7687 | 0.7708 | 1.6573 | -226.5533 | -242.1535 | -2.5558 | -2.5652 |
| 0.2535 | 1.0695 | 100 | 0.5072 | 0.6618 | -1.4593 | 0.8155 | 2.1211 | -233.4590 | -244.4205 | -2.3160 | -2.3489 |
| 0.2927 | 1.6043 | 150 | 0.5305 | 0.2199 | -2.4527 | 0.8065 | 2.6726 | -243.3929 | -248.8394 | -2.2493 | -2.2896 |
| 0.1722 | 2.1390 | 200 | 0.4972 | 0.5435 | -2.1567 | 0.8304 | 2.7003 | -240.4332 | -245.6031 | -2.1267 | -2.1841 |
| 0.1412 | 2.6738 | 250 | 0.5014 | 0.2961 | -2.5802 | 0.8214 | 2.8763 | -244.6681 | -248.0778 | -2.1488 | -2.2053 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.3
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