---
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
  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/5lcdjsus)
# aoi_clip_high_resolution_concate_fusin_crop_each_text

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: 3.4957
- Accuracy: 0.0648

## 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: 20
- eval_batch_size: 20
- seed: 42
- gradient_accumulation_steps: 10
- 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 |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 1.7286        | 5.9821  | 1602  | 3.0151          | 0.0654   |
| 1.6207        | 11.9642 | 3204  | 3.2376          | 0.0665   |
| 1.5399        | 17.9462 | 4806  | 3.2386          | 0.0685   |
| 1.4981        | 23.9283 | 6408  | 3.3545          | 0.0673   |
| 1.4774        | 29.9104 | 8010  | 3.3404          | 0.0677   |
| 1.4648        | 35.8925 | 9612  | 3.4236          | 0.0670   |
| 1.4549        | 41.8745 | 11214 | 3.4689          | 0.0664   |
| 1.4528        | 47.8566 | 12816 | 3.5205          | 0.0659   |
| 1.4538        | 53.8387 | 14418 | 3.4703          | 0.0655   |
| 1.4519        | 59.8208 | 16020 | 3.4957          | 0.0651   |


### Framework versions

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