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--- |
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base_model: microsoft/trocr-base-stage1 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: IS557_TrOCR_AllData |
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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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# IS557_TrOCR_AllData |
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This model is a fine-tuned version of [microsoft/trocr-base-stage1](https://huggingface.co/microsoft/trocr-base-stage1) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0124 |
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- Cer: 0.1764 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 3.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Cer | |
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|:-------------:|:------:|:----:|:---------------:|:------:| |
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| 4.4421 | 0.0708 | 200 | 4.1713 | 0.6172 | |
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| 3.2966 | 0.1415 | 400 | 3.1228 | 0.5064 | |
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| 2.5955 | 0.2123 | 600 | 2.7626 | 0.3949 | |
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| 2.201 | 0.2831 | 800 | 2.4729 | 0.4258 | |
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| 1.5876 | 0.3539 | 1000 | 2.2295 | 0.3097 | |
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| 2.7774 | 0.4246 | 1200 | 2.1112 | 0.3092 | |
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| 2.7995 | 0.4954 | 1400 | 2.1286 | 0.3070 | |
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| 1.5241 | 0.5662 | 1600 | 1.8915 | 0.2534 | |
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| 0.9877 | 0.6369 | 1800 | 1.8091 | 0.2624 | |
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| 1.21 | 0.7077 | 2000 | 1.7322 | 0.2552 | |
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| 1.5582 | 0.7785 | 2200 | 1.6645 | 0.2445 | |
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| 1.1392 | 0.8493 | 2400 | 1.6458 | 0.2294 | |
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| 1.8181 | 0.9200 | 2600 | 1.5874 | 0.2313 | |
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| 1.2517 | 0.9908 | 2800 | 1.5736 | 0.2361 | |
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| 1.2004 | 1.0616 | 3000 | 1.5693 | 0.2344 | |
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| 1.4357 | 1.1323 | 3200 | 1.5447 | 0.2190 | |
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| 1.1354 | 1.2031 | 3400 | 1.4577 | 0.3232 | |
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| 0.853 | 1.2739 | 3600 | 1.4034 | 0.2166 | |
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| 1.4631 | 1.3447 | 3800 | 1.4105 | 0.2093 | |
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| 2.3234 | 1.4154 | 4000 | 1.3813 | 0.2044 | |
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| 0.6976 | 1.4862 | 4200 | 1.3505 | 0.2088 | |
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| 1.4337 | 1.5570 | 4400 | 1.3338 | 0.2079 | |
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| 1.0502 | 1.6277 | 4600 | 1.3044 | 0.1900 | |
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| 1.2216 | 1.6985 | 4800 | 1.2883 | 0.2176 | |
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| 1.0111 | 1.7693 | 5000 | 1.2530 | 0.1977 | |
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| 0.9992 | 1.8401 | 5200 | 1.2245 | 0.2064 | |
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| 0.9941 | 1.9108 | 5400 | 1.2187 | 0.1933 | |
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| 1.4861 | 1.9816 | 5600 | 1.1961 | 0.1827 | |
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| 1.1703 | 2.0524 | 5800 | 1.1776 | 0.1927 | |
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| 0.8935 | 2.1231 | 6000 | 1.1617 | 0.1891 | |
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| 2.5386 | 2.1939 | 6200 | 1.1686 | 0.1823 | |
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| 0.4705 | 2.2647 | 6400 | 1.1259 | 0.1843 | |
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| 1.2777 | 2.3355 | 6600 | 1.1228 | 0.1882 | |
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| 0.6823 | 2.4062 | 6800 | 1.1035 | 0.1787 | |
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| 1.2498 | 2.4770 | 7000 | 1.0976 | 0.1814 | |
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| 0.4579 | 2.5478 | 7200 | 1.0839 | 0.1721 | |
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| 0.9005 | 2.6185 | 7400 | 1.0695 | 0.1817 | |
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| 0.8045 | 2.6893 | 7600 | 1.0513 | 0.1745 | |
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| 1.3044 | 2.7601 | 7800 | 1.0336 | 0.1814 | |
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| 1.0797 | 2.8309 | 8000 | 1.0275 | 0.1846 | |
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| 0.3826 | 2.9016 | 8200 | 1.0178 | 0.1817 | |
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| 0.6175 | 2.9724 | 8400 | 1.0124 | 0.1764 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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