---
base_model: OFA-Sys/chinese-clip-vit-base-patch16
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: aoi_clip_high_resolution_cross_attention_fusin
  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/rursnx15)
# aoi_clip_high_resolution_cross_attention_fusin

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: 4.0266
- Accuracy: 0.0266

## 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: 40
- eval_batch_size: 40
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 200
- 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 |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 2.4856        | 5.9923  | 1866  | 3.6872          | 0.0237   |
| 2.4767        | 11.9846 | 3732  | 3.6874          | 0.0244   |
| 2.4784        | 17.9769 | 5598  | 3.6876          | 0.0247   |
| 2.4728        | 23.9692 | 7464  | 3.6878          | 0.0251   |
| 2.473         | 29.9615 | 9330  | 3.6875          | 0.0255   |
| 2.4621        | 35.9538 | 11196 | 3.7371          | 0.0266   |
| 2.3868        | 41.9461 | 13062 | 3.8208          | 0.0269   |
| 2.3293        | 47.9383 | 14928 | 3.8805          | 0.0268   |
| 2.2917        | 53.9306 | 16794 | 3.9713          | 0.0267   |
| 2.2787        | 59.9229 | 18660 | 4.0266          | 0.0266   |


### Framework versions

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