---
base_model: OFA-Sys/chinese-clip-vit-base-patch16
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: sentance_split_by_time_ocr_concate
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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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/b55yyize)
# sentance_split_by_time_ocr_concate

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: 3.7882
- Accuracy: 0.0654

## 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: 60.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Accuracy |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 2.0902        | 5.9928  | 1866  | 3.0755          | 0.0687   |
| 1.8876        | 11.9855 | 3732  | 3.2740          | 0.0669   |
| 1.763         | 17.9783 | 5598  | 3.2469          | 0.0681   |
| 1.7048        | 23.9711 | 7464  | 3.4242          | 0.0677   |
| 1.6776        | 29.9639 | 9330  | 3.4987          | 0.0674   |
| 1.6518        | 35.9566 | 11196 | 3.5633          | 0.0675   |
| 1.6471        | 41.9494 | 13062 | 3.6389          | 0.0668   |
| 1.6319        | 47.9422 | 14928 | 3.6843          | 0.0663   |
| 1.6325        | 53.9350 | 16794 | 3.7068          | 0.0658   |
| 1.6255        | 59.9277 | 18660 | 3.7882          | 0.0654   |


### Framework versions

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