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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: ser-model-microsoft |
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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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# ser-model-microsoft |
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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: 0.2762 |
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- Precision: 0.6 |
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- Recall: 0.9 |
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- F1: 0.7200 |
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- Accuracy: 0.925 |
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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: 100 |
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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 | 5.0 | 10 | 0.9255 | 0.0 | 0.0 | 0.0 | 0.7 | |
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| No log | 10.0 | 20 | 0.6668 | 0.4444 | 0.4 | 0.4211 | 0.7875 | |
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| No log | 15.0 | 30 | 0.4304 | 0.6667 | 0.8 | 0.7273 | 0.85 | |
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| No log | 20.0 | 40 | 0.4050 | 0.6667 | 0.8 | 0.7273 | 0.85 | |
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| No log | 25.0 | 50 | 0.5639 | 0.8 | 0.8 | 0.8000 | 0.8125 | |
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| No log | 30.0 | 60 | 0.2429 | 0.8 | 0.8 | 0.8000 | 0.925 | |
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| No log | 35.0 | 70 | 0.4434 | 0.6667 | 0.8 | 0.7273 | 0.8625 | |
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| No log | 40.0 | 80 | 0.2817 | 0.6 | 0.9 | 0.7200 | 0.925 | |
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| No log | 45.0 | 90 | 0.2784 | 0.6 | 0.9 | 0.7200 | 0.925 | |
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| No log | 50.0 | 100 | 0.2762 | 0.6 | 0.9 | 0.7200 | 0.925 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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