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--- |
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base_model: kavg/TrOCR-SIN |
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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-Handwritten |
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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-Handwritten |
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This model is a fine-tuned version of [kavg/TrOCR-SIN](https://huggingface.co/kavg/TrOCR-SIN) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.4199 |
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- Cer: 0.5981 |
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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: 32 |
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- eval_batch_size: 32 |
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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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- num_epochs: 100 |
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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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| 1.1305 | 1.72 | 50 | 0.7056 | 2.0648 | |
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| 0.5468 | 3.45 | 100 | 0.7023 | 1.9332 | |
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| 0.0732 | 5.17 | 150 | 0.6624 | 2.2013 | |
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| 0.0995 | 6.9 | 200 | 0.6756 | 2.2015 | |
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| 0.1715 | 8.62 | 250 | 0.6602 | 2.0091 | |
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| 0.1086 | 10.34 | 300 | 0.6672 | 2.2239 | |
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| 0.0798 | 12.07 | 350 | 0.6839 | 2.0926 | |
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| 0.0194 | 13.79 | 400 | 0.6926 | 2.2650 | |
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| 0.0453 | 15.52 | 450 | 0.7223 | 2.4613 | |
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| 0.0579 | 17.24 | 500 | 0.6931 | 2.3523 | |
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| 0.0301 | 18.97 | 550 | 0.6215 | 2.1677 | |
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| 0.0215 | 20.69 | 600 | 0.6602 | 2.2610 | |
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| 0.0112 | 22.41 | 650 | 0.6415 | 2.2070 | |
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| 0.0048 | 24.14 | 700 | 0.6363 | 2.2219 | |
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| 0.0117 | 25.86 | 750 | 0.6609 | 2.2341 | |
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| 0.0034 | 27.59 | 800 | 0.6829 | 2.4177 | |
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| 0.0184 | 29.31 | 850 | 0.6826 | 2.3418 | |
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| 0.0108 | 31.03 | 900 | 0.6682 | 2.3715 | |
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| 0.0152 | 32.76 | 950 | 0.6542 | 2.2079 | |
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| 0.0019 | 34.48 | 1000 | 0.6365 | 2.2173 | |
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| 0.0009 | 36.21 | 1050 | 0.6574 | 2.4185 | |
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| 0.0013 | 37.93 | 1100 | 0.6520 | 2.3515 | |
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| 0.0005 | 39.66 | 1150 | 0.6081 | 2.2393 | |
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| 0.0003 | 41.38 | 1200 | 0.6632 | 2.7642 | |
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| 0.0003 | 43.1 | 1250 | 0.6313 | 2.2789 | |
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| 0.0002 | 44.83 | 1300 | 0.6360 | 2.3862 | |
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| 0.0004 | 46.55 | 1350 | 0.6228 | 2.3372 | |
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| 0.0001 | 48.28 | 1400 | 0.6542 | 2.3822 | |
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| 0.0003 | 50.0 | 1450 | 2.3609 | 0.6480 | |
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| 0.0015 | 51.72 | 1500 | 2.6877 | 0.6520 | |
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| 0.0352 | 53.45 | 1550 | 3.3146 | 0.6826 | |
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| 0.0085 | 55.17 | 1600 | 2.8430 | 0.6901 | |
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| 0.0004 | 56.9 | 1650 | 3.0267 | 0.6654 | |
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| 0.0006 | 58.62 | 1700 | 2.3768 | 0.6589 | |
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| 0.0013 | 60.34 | 1750 | 2.4242 | 0.6717 | |
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| 0.0033 | 62.07 | 1800 | 2.5133 | 0.6512 | |
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| 0.0002 | 63.79 | 1850 | 2.4018 | 0.6604 | |
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| 0.0006 | 65.52 | 1900 | 2.8438 | 0.6679 | |
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| 0.0006 | 67.24 | 1950 | 2.4073 | 0.6482 | |
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| 0.0001 | 68.97 | 2000 | 2.7375 | 0.6510 | |
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| 0.0002 | 70.69 | 2050 | 2.4250 | 0.6146 | |
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| 0.0001 | 72.41 | 2100 | 2.7045 | 0.6604 | |
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| 0.0001 | 74.14 | 2150 | 3.3714 | 0.6597 | |
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| 0.0001 | 75.86 | 2200 | 2.9585 | 0.6936 | |
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| 0.0 | 77.59 | 2250 | 2.5378 | 0.6131 | |
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| 0.0136 | 79.31 | 2300 | 2.6351 | 0.6146 | |
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| 0.0 | 81.03 | 2350 | 2.5288 | 0.6116 | |
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| 0.0001 | 82.76 | 2400 | 2.4601 | 0.6338 | |
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| 0.0002 | 84.48 | 2450 | 2.4646 | 0.6248 | |
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| 0.0 | 86.21 | 2500 | 2.8099 | 0.6542 | |
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| 0.0 | 87.93 | 2550 | 2.7981 | 0.6781 | |
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| 0.0 | 89.66 | 2600 | 2.4607 | 0.6200 | |
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| 0.0 | 91.38 | 2650 | 2.5363 | 0.6612 | |
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| 0.0096 | 93.1 | 2700 | 2.4875 | 0.6113 | |
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| 0.0 | 94.83 | 2750 | 2.4574 | 0.6268 | |
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| 0.0 | 96.55 | 2800 | 2.4199 | 0.5981 | |
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| 0.0 | 98.28 | 2850 | 2.4452 | 0.6181 | |
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| 0.0 | 100.0 | 2900 | 2.4369 | 0.6036 | |
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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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