---
base_model: OFA-Sys/chinese-clip-vit-base-patch16
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: sentance_split_by_time_ocr_concate_2
  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/skkco61i)
# sentance_split_by_time_ocr_concate_2

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: 3.7759
- Accuracy: 0.0760

## 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 |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 2.077         | 5.9928  | 1866  | 3.0593          | 0.0767   |
| 1.8747        | 11.9855 | 3732  | 3.1969          | 0.0788   |
| 1.7613        | 17.9783 | 5598  | 3.2275          | 0.0782   |
| 1.703         | 23.9711 | 7464  | 3.3677          | 0.0788   |
| 1.676         | 29.9639 | 9330  | 3.4368          | 0.0784   |
| 1.6495        | 35.9566 | 11196 | 3.5520          | 0.0783   |
| 1.6449        | 41.9494 | 13062 | 3.5562          | 0.0781   |
| 1.6293        | 47.9422 | 14928 | 3.6218          | 0.0775   |
| 1.6301        | 53.9350 | 16794 | 3.7435          | 0.0770   |
| 1.6232        | 59.9277 | 18660 | 3.7759          | 0.0765   |


### Framework versions

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