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--- |
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license: cc-by-nc-sa-4.0 |
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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: model-2024-06-06 |
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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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# model-2024-06-06 |
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This model is a fine-tuned version of [microsoft/layoutlmv3-large](https://huggingface.co/microsoft/layoutlmv3-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5257 |
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- Precision: 0.7422 |
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- Recall: 0.7427 |
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- F1: 0.7424 |
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- Accuracy: 0.8617 |
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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 | 0.6 | 100 | 1.4725 | 0.2387 | 0.0987 | 0.1396 | 0.6316 | |
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| No log | 1.19 | 200 | 0.9815 | 0.5362 | 0.434 | 0.4797 | 0.7585 | |
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| No log | 1.79 | 300 | 0.7596 | 0.6422 | 0.5707 | 0.6043 | 0.8071 | |
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| No log | 2.38 | 400 | 0.6719 | 0.6739 | 0.6433 | 0.6583 | 0.8240 | |
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| 1.1397 | 2.98 | 500 | 0.5865 | 0.7118 | 0.7013 | 0.7065 | 0.8429 | |
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| 1.1397 | 3.57 | 600 | 0.5910 | 0.7293 | 0.722 | 0.7256 | 0.8505 | |
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| 1.1397 | 4.17 | 700 | 0.5456 | 0.7373 | 0.726 | 0.7316 | 0.8524 | |
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| 1.1397 | 4.76 | 800 | 0.5343 | 0.7376 | 0.7327 | 0.7351 | 0.8557 | |
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| 1.1397 | 5.36 | 900 | 0.5327 | 0.7283 | 0.7487 | 0.7383 | 0.8569 | |
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| 0.4593 | 5.95 | 1000 | 0.5257 | 0.7422 | 0.7427 | 0.7424 | 0.8617 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.13.3 |
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