---
base_model: OFA-Sys/chinese-clip-vit-base-patch16
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: aoi_clip_high_resolution_concate_fusin_crop_each_text_512
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/shark_meow_team/huggingface/runs/9tw3ng1k)
# aoi_clip_high_resolution_concate_fusin_crop_each_text_512

This model is a fine-tuned version of [OFA-Sys/chinese-clip-vit-base-patch16](https://huggingface.co/OFA-Sys/chinese-clip-vit-base-patch16) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5539
- Accuracy: 0.0669

## 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-05
- train_batch_size: 15
- eval_batch_size: 20
- seed: 42
- gradient_accumulation_steps: 14
- total_train_batch_size: 210
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 60.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.5814        | 6.0   | 1530  | 3.0257          | 0.0726   |
| 1.4807        | 12.0  | 3060  | 3.2677          | 0.0712   |
| 1.4075        | 18.0  | 4590  | 3.3332          | 0.0703   |
| 1.3618        | 24.0  | 6120  | 3.2491          | 0.0692   |
| 1.3396        | 30.0  | 7650  | 3.3756          | 0.0690   |
| 1.3298        | 36.0  | 9180  | 3.5386          | 0.0678   |
| 1.324         | 42.0  | 10710 | 3.5245          | 0.0675   |
| 1.3177        | 48.0  | 12240 | 3.5136          | 0.0671   |
| 1.3181        | 54.0  | 13770 | 3.4984          | 0.0669   |
| 1.3117        | 60.0  | 15300 | 3.5539          | 0.0669   |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1