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--- |
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library_name: transformers |
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base_model: layoutlmv3 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- mp-02/sroie |
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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-base-sroie |
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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: mp-02/sroie |
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type: mp-02/sroie |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.9469573706475757 |
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- name: Recall |
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type: recall |
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value: 0.9648541114058355 |
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- name: F1 |
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type: f1 |
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value: 0.9558219740515684 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9863575751359114 |
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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-base-sroie |
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This model is a fine-tuned version of [layoutlmv3](https://huggingface.co/layoutlmv3) on the mp-02/sroie dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0526 |
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- Precision: 0.9470 |
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- Recall: 0.9649 |
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- F1: 0.9558 |
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- Accuracy: 0.9864 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 3000 |
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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 | 2.5 | 100 | 0.0806 | 0.9001 | 0.9377 | 0.9185 | 0.9759 | |
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| No log | 5.0 | 200 | 0.0541 | 0.9392 | 0.9576 | 0.9483 | 0.9840 | |
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| No log | 7.5 | 300 | 0.0515 | 0.9368 | 0.9629 | 0.9496 | 0.9844 | |
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| No log | 10.0 | 400 | 0.0515 | 0.9450 | 0.9622 | 0.9535 | 0.9856 | |
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| 0.0717 | 12.5 | 500 | 0.0526 | 0.9470 | 0.9649 | 0.9558 | 0.9864 | |
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| 0.0717 | 15.0 | 600 | 0.0558 | 0.9353 | 0.9685 | 0.9516 | 0.9849 | |
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| 0.0717 | 17.5 | 700 | 0.0668 | 0.9408 | 0.9635 | 0.9520 | 0.9852 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu118 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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