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--- |
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base_model: kavg/TrOCR-SIN-DeiT |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: TrOCR-SIN-DeiT-Handwritten-Beam10 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# TrOCR-SIN-DeiT-Handwritten-Beam10 |
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This model is a fine-tuned version of [kavg/TrOCR-SIN-DeiT](https://huggingface.co/kavg/TrOCR-SIN-DeiT) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2754 |
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- Cer: 0.5246 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- training_steps: 2400 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Cer | Validation Loss | |
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|:-------------:|:-----:|:----:|:------:|:---------------:| |
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| 0.9957 | 1.75 | 100 | 0.6176 | 1.6796 | |
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| 0.0678 | 3.51 | 200 | 0.5996 | 1.7777 | |
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| 0.1315 | 5.26 | 300 | 0.6794 | 2.1444 | |
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| 0.0668 | 7.02 | 400 | 0.6363 | 2.0162 | |
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| 0.0656 | 8.77 | 500 | 0.6046 | 1.9573 | |
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| 0.0612 | 10.53 | 600 | 0.6330 | 1.9388 | |
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| 0.0454 | 12.28 | 700 | 0.6679 | 3.0649 | |
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| 0.004 | 14.04 | 800 | 0.5814 | 2.0252 | |
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| 0.0034 | 15.79 | 900 | 0.5492 | 2.0399 | |
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| 0.0336 | 17.54 | 1000 | 0.6041 | 2.9769 | |
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| 0.0135 | 19.3 | 1100 | 0.5742 | 1.9405 | |
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| 0.0012 | 21.05 | 1200 | 0.5959 | 2.5722 | |
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| 0.0143 | 22.81 | 1300 | 0.5527 | 2.0862 | |
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| 0.0018 | 24.56 | 1400 | 0.5764 | 2.4146 | |
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| 0.0064 | 26.32 | 1500 | 0.5647 | 2.0710 | |
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| 0.0006 | 28.07 | 1600 | 0.5472 | 2.1849 | |
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| 0.0004 | 29.82 | 1700 | 0.5547 | 2.4497 | |
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| 0.0001 | 31.58 | 1800 | 0.5430 | 2.0830 | |
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| 0.0215 | 33.33 | 1900 | 0.5560 | 2.5979 | |
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| 0.0 | 35.09 | 2000 | 0.5525 | 2.4792 | |
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| 0.0 | 36.84 | 2100 | 0.5428 | 2.4779 | |
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| 0.0 | 38.6 | 2200 | 0.5438 | 2.7873 | |
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| 0.0 | 40.35 | 2300 | 0.5552 | 2.9236 | |
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| 0.0 | 42.11 | 2400 | 0.5246 | 2.2754 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.1 |
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