---
base_model: OFA-Sys/chinese-clip-vit-base-patch16
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: aoi_clip_high_resolution_text_only_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/gtoodtwl)
# aoi_clip_high_resolution_text_only_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: 3.2382
- Accuracy: 0.1291

## 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: 50
- eval_batch_size: 20
- seed: 42
- gradient_accumulation_steps: 4
- 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 |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 2.5113        | 9.9839  | 3110  | 2.8518          | 0.1566   |
| 2.3003        | 19.9679 | 6220  | 3.0242          | 0.1476   |
| 2.2124        | 29.9518 | 9330  | 3.1246          | 0.1404   |
| 2.1682        | 39.9358 | 12440 | 3.1806          | 0.1371   |
| 2.1384        | 49.9197 | 15550 | 3.2024          | 0.1342   |
| 2.1246        | 59.9037 | 18660 | 3.2168          | 0.1323   |
| 2.1121        | 69.8876 | 21770 | 3.2209          | 0.1313   |
| 2.0987        | 79.8716 | 24880 | 3.2137          | 0.1307   |
| 2.0986        | 89.8555 | 27990 | 3.2374          | 0.1301   |
| 2.0962        | 99.8395 | 31100 | 3.2382          | 0.1295   |


### Framework versions

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