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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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- funsd-layoutlmv3 |
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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: test |
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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: funsd-layoutlmv3 |
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type: funsd-layoutlmv3 |
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config: funsd |
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split: test |
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args: funsd |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.8808265257087938 |
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- name: Recall |
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type: recall |
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value: 0.910581222056632 |
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- name: F1 |
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type: f1 |
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value: 0.895456765999023 |
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- name: Accuracy |
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type: accuracy |
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value: 0.8507072387970998 |
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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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# test |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the funsd-layoutlmv3 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5799 |
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- Precision: 0.8808 |
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- Recall: 0.9106 |
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- F1: 0.8955 |
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- Accuracy: 0.8507 |
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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 | 1.3333 | 100 | 0.6686 | 0.7452 | 0.8251 | 0.7831 | 0.7535 | |
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| No log | 2.6667 | 200 | 0.4724 | 0.8064 | 0.8713 | 0.8376 | 0.8389 | |
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| No log | 4.0 | 300 | 0.4922 | 0.8612 | 0.8942 | 0.8774 | 0.8481 | |
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| No log | 5.3333 | 400 | 0.4632 | 0.8587 | 0.8997 | 0.8787 | 0.8521 | |
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| 0.544 | 6.6667 | 500 | 0.4850 | 0.8632 | 0.9031 | 0.8827 | 0.8474 | |
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| 0.544 | 8.0 | 600 | 0.5024 | 0.8744 | 0.8992 | 0.8866 | 0.8451 | |
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| 0.544 | 9.3333 | 700 | 0.5394 | 0.8768 | 0.9155 | 0.8957 | 0.8565 | |
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| 0.544 | 10.6667 | 800 | 0.5647 | 0.8800 | 0.9146 | 0.8970 | 0.8550 | |
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| 0.544 | 12.0 | 900 | 0.5798 | 0.8847 | 0.9106 | 0.8974 | 0.8545 | |
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| 0.1288 | 13.3333 | 1000 | 0.5799 | 0.8808 | 0.9106 | 0.8955 | 0.8507 | |
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### Framework versions |
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- Transformers 4.41.0.dev0 |
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- Pytorch 2.1.1+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.19.1 |
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