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---
tags:
- image-to-text
language: ar
model-index:
- name: ArOCR
results:
- task:
name: Optical Charater Recogntion
type: image-to-text
metrics:
- name: Test CER
type: cer
value: 0.02
---
<!-- 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. -->
# ArOCR
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0407
- Cer: 0.0200
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.6164 | 0.59 | 1000 | 1.4109 | 0.5793 |
| 0.3434 | 1.18 | 2000 | 0.3876 | 0.2176 |
| 0.1679 | 1.77 | 3000 | 0.2262 | 0.1186 |
| 0.0816 | 2.37 | 4000 | 0.1274 | 0.0634 |
| 0.0421 | 2.96 | 5000 | 0.0817 | 0.0381 |
| 0.0067 | 3.55 | 6000 | 0.0520 | 0.0265 |
| 0.0044 | 4.14 | 7000 | 0.0469 | 0.0215 |
| 0.0027 | 4.73 | 8000 | 0.0407 | 0.0200 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.9.1
- Datasets 2.1.0
- Tokenizers 0.11.6
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