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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: MRR-NER-08-09-Layoutlmv3 |
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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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# MRR-NER-08-09-Layoutlmv3 |
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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: 0.0175 |
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- Precision: 0.8367 |
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- Recall: 0.9111 |
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- F1: 0.8723 |
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- Accuracy: 0.9960 |
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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: 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 | 8.33 | 100 | 0.2585 | 0.1667 | 0.0222 | 0.0392 | 0.9607 | |
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| No log | 16.67 | 200 | 0.1281 | 0.4783 | 0.2444 | 0.3235 | 0.9727 | |
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| No log | 25.0 | 300 | 0.0821 | 0.3696 | 0.3778 | 0.3736 | 0.9767 | |
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| No log | 33.33 | 400 | 0.0493 | 0.5111 | 0.5111 | 0.5111 | 0.9813 | |
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| 0.2244 | 41.67 | 500 | 0.0330 | 0.625 | 0.7778 | 0.6931 | 0.9913 | |
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| 0.2244 | 50.0 | 600 | 0.0272 | 0.6909 | 0.8444 | 0.7600 | 0.9927 | |
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| 0.2244 | 58.33 | 700 | 0.0218 | 0.7843 | 0.8889 | 0.8333 | 0.9953 | |
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| 0.2244 | 66.67 | 800 | 0.0190 | 0.7547 | 0.8889 | 0.8163 | 0.9947 | |
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| 0.2244 | 75.0 | 900 | 0.0158 | 0.8936 | 0.9333 | 0.9130 | 0.9973 | |
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| 0.038 | 83.33 | 1000 | 0.0175 | 0.8367 | 0.9111 | 0.8723 | 0.9960 | |
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### Framework versions |
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- Transformers 4.34.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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