---
base_model: OFA-Sys/chinese-clip-vit-base-patch16
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: aoi_clip_high_resolution_crossAttenttionFusion_fusin_gpt_new_sampler
  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/cru2aevs)
# aoi_clip_high_resolution_crossAttenttionFusion_fusin_gpt_new_sampler

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: 5.3131
- Accuracy: 0.0559

## 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: 25
- eval_batch_size: 20
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 200
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 200.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step  | Validation Loss | Accuracy |
|:-------------:|:--------:|:-----:|:---------------:|:--------:|
| 2.152         | 19.9759  | 6220  | 3.0212          | 0.0537   |
| 1.9424        | 39.9518  | 12440 | 3.4495          | 0.0563   |
| 1.7646        | 59.9277  | 18660 | 3.9469          | 0.0561   |
| 1.6901        | 79.9037  | 24880 | 4.2354          | 0.0550   |
| 1.6562        | 99.8796  | 31100 | 4.6732          | 0.0548   |
| 1.6398        | 119.8555 | 37320 | 4.8612          | 0.0550   |
| 1.6289        | 139.8314 | 43540 | 4.8784          | 0.0550   |
| 1.6192        | 159.8073 | 49760 | 5.2516          | 0.0554   |
| 1.6163        | 179.7832 | 55980 | 5.2837          | 0.0558   |
| 1.6165        | 199.7591 | 62200 | 5.3131          | 0.0558   |


### Framework versions

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