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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 |
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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-funsd |
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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 |
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type: funsd |
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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: 0.7467652495378928 |
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- name: Recall |
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type: recall |
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value: 0.8027819175360159 |
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- name: F1 |
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type: f1 |
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value: 0.7737610725401005 |
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- name: Accuracy |
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type: accuracy |
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value: 0.8188517770117675 |
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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-funsd |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the funsd dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5984 |
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- Precision: 0.7468 |
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- Recall: 0.8028 |
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- F1: 0.7738 |
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- Accuracy: 0.8189 |
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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: 1 |
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- eval_batch_size: 1 |
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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 | 0.67 | 100 | 1.0197 | 0.5025 | 0.5981 | 0.5462 | 0.6622 | |
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| No log | 1.34 | 200 | 0.6833 | 0.6203 | 0.7238 | 0.6680 | 0.7608 | |
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| No log | 2.01 | 300 | 0.6237 | 0.6401 | 0.7794 | 0.7030 | 0.7846 | |
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| No log | 2.68 | 400 | 0.6028 | 0.6892 | 0.7392 | 0.7133 | 0.7771 | |
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| 0.8343 | 3.36 | 500 | 0.5948 | 0.7175 | 0.7884 | 0.7512 | 0.7991 | |
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| 0.8343 | 4.03 | 600 | 0.5953 | 0.7135 | 0.8028 | 0.7555 | 0.7961 | |
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| 0.8343 | 4.7 | 700 | 0.5925 | 0.7354 | 0.7953 | 0.7642 | 0.8174 | |
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| 0.8343 | 5.37 | 800 | 0.6055 | 0.7397 | 0.7933 | 0.7656 | 0.8134 | |
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| 0.8343 | 6.04 | 900 | 0.5940 | 0.7535 | 0.8077 | 0.7797 | 0.8199 | |
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| 0.3468 | 6.71 | 1000 | 0.5984 | 0.7468 | 0.8028 | 0.7738 | 0.8189 | |
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### Framework versions |
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- Transformers 4.35.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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