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---
base_model: OFA-Sys/chinese-clip-vit-base-patch16
tags:
- generated_from_trainer
model-index:
- name: aoi_clip_clean
  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. -->

[<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/n13f9o9o)
# aoi_clip_clean

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: 5.6248

## 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: 44
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 120.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 0.2626        | 12.0  | 17748  | 6.2362          |
| 0.057         | 24.0  | 35496  | 6.3541          |
| 0.0428        | 36.0  | 53244  | 6.0895          |
| 0.0359        | 48.0  | 70992  | 6.1071          |
| 0.0312        | 60.0  | 88740  | 5.9994          |
| 0.0287        | 72.0  | 106488 | 5.8543          |
| 0.0262        | 84.0  | 124236 | 5.7595          |
| 0.0246        | 96.0  | 141984 | 5.7167          |
| 0.0227        | 108.0 | 159732 | 5.6840          |
| 0.0215        | 120.0 | 177480 | 5.6248          |


### Framework versions

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