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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-funsd2 |
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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-funsd2 |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6633 |
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- Precision: 0.9027 |
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- Recall: 0.9090 |
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- F1: 0.9058 |
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- Accuracy: 0.8500 |
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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: 5e-05 |
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- train_batch_size: 14 |
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- eval_batch_size: 14 |
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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: 120 |
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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 | 0.9091 | 10 | 0.9825 | 0.5685 | 0.6133 | 0.5901 | 0.6804 | |
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| No log | 1.8182 | 20 | 0.6492 | 0.7647 | 0.8215 | 0.7921 | 0.7781 | |
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| No log | 2.7273 | 30 | 0.5079 | 0.8037 | 0.8635 | 0.8326 | 0.8370 | |
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| No log | 3.6364 | 40 | 0.5371 | 0.8600 | 0.8924 | 0.8759 | 0.8428 | |
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| No log | 4.5455 | 50 | 0.5696 | 0.8753 | 0.8968 | 0.8859 | 0.8348 | |
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| No log | 5.4545 | 60 | 0.6309 | 0.8733 | 0.8863 | 0.8797 | 0.8272 | |
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| No log | 6.3636 | 70 | 0.6272 | 0.8878 | 0.9003 | 0.8940 | 0.8494 | |
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| No log | 7.2727 | 80 | 0.6168 | 0.9025 | 0.9151 | 0.9088 | 0.8688 | |
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| No log | 8.1818 | 90 | 0.6458 | 0.9094 | 0.9134 | 0.9114 | 0.8588 | |
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| No log | 9.0909 | 100 | 0.6830 | 0.8985 | 0.9064 | 0.9024 | 0.8490 | |
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| No log | 10.0 | 110 | 0.6325 | 0.9086 | 0.9221 | 0.9153 | 0.8502 | |
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| No log | 10.9091 | 120 | 0.6633 | 0.9027 | 0.9090 | 0.9058 | 0.8500 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0+cu118 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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