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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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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-language-levels-v3-4000 |
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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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# layoutlmv3-finetuned-language-levels-v3-4000 |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0209 |
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- Precision: 1.0 |
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- Recall: 1.0 |
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- F1: 1.0 |
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- Accuracy: 1.0 |
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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 | 0.0290 | 100 | 0.8242 | 0.9549 | 0.9520 | 0.9534 | 0.7171 | |
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| No log | 0.0579 | 200 | 0.5708 | 0.9636 | 0.9772 | 0.9703 | 0.7951 | |
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| No log | 0.0869 | 300 | 0.3493 | 0.9993 | 0.9993 | 0.9993 | 0.8839 | |
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| No log | 0.1158 | 400 | 0.1466 | 0.9998 | 0.9998 | 0.9998 | 0.9752 | |
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| 0.6024 | 0.1448 | 500 | 0.0689 | 0.9965 | 0.9972 | 0.9969 | 0.9823 | |
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| 0.6024 | 0.1738 | 600 | 0.0442 | 1.0 | 1.0 | 1.0 | 0.9946 | |
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| 0.6024 | 0.2027 | 700 | 0.0360 | 1.0 | 1.0 | 1.0 | 0.9847 | |
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| 0.6024 | 0.2317 | 800 | 0.0280 | 1.0 | 1.0 | 1.0 | 0.9972 | |
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| 0.6024 | 0.2606 | 900 | 0.0247 | 1.0 | 1.0 | 1.0 | 0.9953 | |
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| 0.0516 | 0.2896 | 1000 | 0.0209 | 1.0 | 1.0 | 1.0 | 1.0 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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