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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: 0.8889970788704966 |
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- name: Recall |
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type: recall |
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value: 0.907103825136612 |
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- name: F1 |
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type: f1 |
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value: 0.8979591836734693 |
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- name: Accuracy |
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type: accuracy |
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value: 0.8665161060263877 |
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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: 0.5474 |
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- Precision: 0.8890 |
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- Recall: 0.9071 |
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- F1: 0.8980 |
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- Accuracy: 0.8665 |
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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 | 1.33 | 100 | 0.5976 | 0.7412 | 0.8296 | 0.7829 | 0.8001 | |
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| No log | 2.67 | 200 | 0.5019 | 0.8259 | 0.8698 | 0.8473 | 0.8269 | |
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| No log | 4.0 | 300 | 0.4829 | 0.8701 | 0.8982 | 0.8839 | 0.8540 | |
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| No log | 5.33 | 400 | 0.4490 | 0.8829 | 0.9141 | 0.8982 | 0.8725 | |
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| 0.5303 | 6.67 | 500 | 0.5120 | 0.8721 | 0.9046 | 0.8881 | 0.8574 | |
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| 0.5303 | 8.0 | 600 | 0.5212 | 0.8802 | 0.9011 | 0.8905 | 0.8644 | |
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| 0.5303 | 9.33 | 700 | 0.5447 | 0.8918 | 0.9086 | 0.9001 | 0.8559 | |
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| 0.5303 | 10.67 | 800 | 0.5304 | 0.8875 | 0.9056 | 0.8965 | 0.8713 | |
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| 0.5303 | 12.0 | 900 | 0.5496 | 0.8878 | 0.9081 | 0.8978 | 0.8630 | |
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| 0.1291 | 13.33 | 1000 | 0.5474 | 0.8890 | 0.9071 | 0.8980 | 0.8665 | |
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### Framework versions |
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- Transformers 4.39.0.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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