---
base_model: OFA-Sys/chinese-clip-vit-base-patch16
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: aoi_clip_high_resolution_concate_fusin_gpt
  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/f4ofem3j)
# aoi_clip_high_resolution_concate_fusin_gpt

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: 4.2052
- Accuracy: 0.0734

## 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: 20
- 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: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Accuracy |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 2.3923        | 9.9872  | 3110  | 3.0972          | 0.0765   |
| 2.1272        | 19.9743 | 6220  | 3.5858          | 0.0782   |
| 1.9949        | 29.9615 | 9330  | 3.6033          | 0.0785   |
| 1.957         | 39.9486 | 12440 | 3.7208          | 0.0769   |
| 1.9313        | 49.9358 | 15550 | 3.8174          | 0.0759   |
| 1.9255        | 59.9229 | 18660 | 3.9145          | 0.0748   |
| 1.9179        | 69.9101 | 21770 | 4.0367          | 0.0746   |
| 1.9133        | 79.8972 | 24880 | 4.0690          | 0.0740   |
| 1.9102        | 89.8844 | 27990 | 4.1227          | 0.0737   |
| 1.9084        | 99.8715 | 31100 | 4.2052          | 0.0734   |


### Framework versions

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