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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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- not-lain/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-finetuned-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: not-lain/sroie |
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type: not-lain/sroie |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.9515865227347072 |
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- name: Recall |
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type: recall |
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value: 0.9645225464190982 |
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- name: F1 |
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type: f1 |
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value: 0.9580108677753993 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9870755974971792 |
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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-sroie |
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This model is a fine-tuned version of [layoutlmv3](https://huggingface.co/layoutlmv3) on the not-lain/sroie dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0596 |
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- Precision: 0.9516 |
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- Recall: 0.9645 |
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- F1: 0.9580 |
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- Accuracy: 0.9871 |
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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: 10 |
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- eval_batch_size: 10 |
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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 | 1.5873 | 100 | 0.0548 | 0.9415 | 0.9453 | 0.9434 | 0.9830 | |
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| No log | 3.1746 | 200 | 0.0531 | 0.9377 | 0.9625 | 0.9499 | 0.9847 | |
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| No log | 4.7619 | 300 | 0.0550 | 0.9414 | 0.9595 | 0.9504 | 0.9851 | |
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| No log | 6.3492 | 400 | 0.0560 | 0.9500 | 0.9645 | 0.9572 | 0.9868 | |
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| 0.0464 | 7.9365 | 500 | 0.0596 | 0.9516 | 0.9645 | 0.9580 | 0.9871 | |
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| 0.0464 | 9.5238 | 600 | 0.0630 | 0.9502 | 0.9622 | 0.9562 | 0.9865 | |
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| 0.0464 | 11.1111 | 700 | 0.0707 | 0.9489 | 0.9658 | 0.9573 | 0.9868 | |
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| 0.0464 | 12.6984 | 800 | 0.0726 | 0.9515 | 0.9629 | 0.9572 | 0.9868 | |
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| 0.0464 | 14.2857 | 900 | 0.0765 | 0.9510 | 0.9652 | 0.9580 | 0.9871 | |
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| 0.0048 | 15.8730 | 1000 | 0.0773 | 0.9500 | 0.9645 | 0.9572 | 0.9868 | |
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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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