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--- |
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license: cc-by-nc-sa-4.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- data_cartas_layoutv3 |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: layoutlmv3-finetuned-letter_100 |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: data_cartas_layoutv3 |
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type: data_cartas_layoutv3 |
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config: default |
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split: test |
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args: default |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.7411894273127754 |
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- name: Recall |
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type: recall |
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value: 0.8672680412371134 |
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- name: F1 |
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type: f1 |
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value: 0.7992874109263659 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9631952889969916 |
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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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# layoutlmv3-finetuned-letter_100 |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the data_cartas_layoutv3 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1884 |
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- Precision: 0.7412 |
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- Recall: 0.8673 |
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- F1: 0.7993 |
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- Accuracy: 0.9632 |
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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-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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: 3000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 3.57 | 250 | 0.4503 | 0.2934 | 0.2242 | 0.2542 | 0.8928 | |
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| 0.5521 | 7.14 | 500 | 0.2833 | 0.4291 | 0.4639 | 0.4458 | 0.9209 | |
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| 0.5521 | 10.71 | 750 | 0.2116 | 0.5702 | 0.6753 | 0.6183 | 0.9437 | |
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| 0.173 | 14.29 | 1000 | 0.1786 | 0.6414 | 0.7835 | 0.7053 | 0.9562 | |
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| 0.173 | 17.86 | 1250 | 0.1772 | 0.6815 | 0.8492 | 0.7562 | 0.9581 | |
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| 0.077 | 21.43 | 1500 | 0.1737 | 0.7144 | 0.8737 | 0.7861 | 0.9616 | |
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| 0.077 | 25.0 | 1750 | 0.1768 | 0.7311 | 0.8724 | 0.7955 | 0.9615 | |
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| 0.0441 | 28.57 | 2000 | 0.1694 | 0.7726 | 0.8273 | 0.7990 | 0.9646 | |
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| 0.0441 | 32.14 | 2250 | 0.1874 | 0.7400 | 0.8621 | 0.7964 | 0.9620 | |
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| 0.0293 | 35.71 | 2500 | 0.1862 | 0.7321 | 0.8698 | 0.7951 | 0.9622 | |
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| 0.0293 | 39.29 | 2750 | 0.1887 | 0.7332 | 0.8711 | 0.7962 | 0.9620 | |
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| 0.0237 | 42.86 | 3000 | 0.1884 | 0.7412 | 0.8673 | 0.7993 | 0.9632 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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