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--- |
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license: cc-by-nc-sa-4.0 |
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base_model: microsoft/layoutlmv3-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- data_loader |
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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: models |
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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_loader |
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type: data_loader |
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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: 0.8940149625935162 |
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- name: Recall |
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type: recall |
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value: 0.9168797953964194 |
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- name: F1 |
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type: f1 |
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value: 0.9053030303030304 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9743718592964824 |
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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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# models |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the data_loader dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1595 |
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- Precision: 0.8940 |
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- Recall: 0.9169 |
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- F1: 0.9053 |
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- Accuracy: 0.9744 |
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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: 1e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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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: 1000 |
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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 | 2.5 | 100 | 0.1926 | 0.7730 | 0.8274 | 0.7993 | 0.9452 | |
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| No log | 5.0 | 200 | 0.1342 | 0.8285 | 0.8708 | 0.8491 | 0.9583 | |
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| No log | 7.5 | 300 | 0.1217 | 0.8758 | 0.9015 | 0.8885 | 0.9693 | |
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| No log | 10.0 | 400 | 0.1157 | 0.9082 | 0.9233 | 0.9157 | 0.9769 | |
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| 0.15 | 12.5 | 500 | 0.1310 | 0.9011 | 0.9092 | 0.9052 | 0.9744 | |
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| 0.15 | 15.0 | 600 | 0.1583 | 0.8682 | 0.9015 | 0.8846 | 0.9693 | |
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| 0.15 | 17.5 | 700 | 0.1628 | 0.8867 | 0.9105 | 0.8984 | 0.9724 | |
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| 0.15 | 20.0 | 800 | 0.1594 | 0.8945 | 0.9220 | 0.9081 | 0.9749 | |
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| 0.15 | 22.5 | 900 | 0.1579 | 0.8940 | 0.9169 | 0.9053 | 0.9744 | |
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| 0.0047 | 25.0 | 1000 | 0.1595 | 0.8940 | 0.9169 | 0.9053 | 0.9744 | |
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### Framework versions |
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- Transformers 4.40.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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