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---
library_name: transformers
base_model: OFA-Sys/chinese-clip-vit-base-patch16
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: sentance_split_by_aoi_ocr_None_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. -->
# sentance_split_by_aoi_ocr_None_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: 3.4765
- Accuracy: 0.1927
## 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.2383 | 5.9676 | 276 | 2.6388 | 0.2417 |
| 0.9769 | 11.9351 | 552 | 2.8174 | 0.2247 |
| 0.8157 | 17.9027 | 828 | 3.1486 | 0.2148 |
| 0.7322 | 23.8703 | 1104 | 3.3020 | 0.2080 |
| 0.6777 | 29.8378 | 1380 | 3.3933 | 0.2026 |
| 0.6466 | 35.8054 | 1656 | 3.4180 | 0.1995 |
| 0.6273 | 41.7730 | 1932 | 3.4385 | 0.1971 |
| 0.6188 | 47.7405 | 2208 | 3.4671 | 0.1953 |
| 0.6051 | 53.7081 | 2484 | 3.4631 | 0.1944 |
| 0.6049 | 59.6757 | 2760 | 3.4765 | 0.1935 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.20.0
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