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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/cord-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-cord-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/cord-sroie |
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type: mp-02/cord-sroie |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.9105022831050228 |
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- name: Recall |
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type: recall |
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value: 0.9447998104714522 |
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- name: F1 |
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type: f1 |
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value: 0.9273340309266364 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9738126147097005 |
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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-cord-sroie |
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This model is a fine-tuned version of [layoutlmv3](https://huggingface.co/layoutlmv3) on the mp-02/cord-sroie dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0936 |
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- Precision: 0.9105 |
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- Recall: 0.9448 |
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- F1: 0.9273 |
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- Accuracy: 0.9738 |
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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: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- training_steps: 4000 |
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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 | 0.7937 | 100 | 0.4396 | 0.6271 | 0.6015 | 0.6140 | 0.9064 | |
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| No log | 1.5873 | 200 | 0.2500 | 0.8669 | 0.8394 | 0.8529 | 0.9508 | |
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| No log | 2.3810 | 300 | 0.1517 | 0.8682 | 0.9050 | 0.8862 | 0.9634 | |
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| No log | 3.1746 | 400 | 0.1346 | 0.8694 | 0.9339 | 0.9005 | 0.9645 | |
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| 0.6691 | 3.9683 | 500 | 0.0943 | 0.9369 | 0.9325 | 0.9347 | 0.9778 | |
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| 0.6691 | 4.7619 | 600 | 0.0922 | 0.9049 | 0.9491 | 0.9265 | 0.9742 | |
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| 0.6691 | 5.5556 | 700 | 0.1106 | 0.8913 | 0.9540 | 0.9216 | 0.9717 | |
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| 0.6691 | 6.3492 | 800 | 0.0875 | 0.9091 | 0.9552 | 0.9316 | 0.9755 | |
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| 0.6691 | 7.1429 | 900 | 0.0958 | 0.8977 | 0.9623 | 0.9289 | 0.9743 | |
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| 0.1055 | 7.9365 | 1000 | 0.0936 | 0.9105 | 0.9448 | 0.9273 | 0.9738 | |
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| 0.1055 | 8.7302 | 1100 | 0.1035 | 0.9289 | 0.9415 | 0.9352 | 0.9766 | |
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| 0.1055 | 9.5238 | 1200 | 0.1115 | 0.9081 | 0.9507 | 0.9289 | 0.9739 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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