End of training
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README.md
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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: LayoutLMv3_5_entities_filtred_12
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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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# LayoutLMv3_5_entities_filtred_12
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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: 0.1405
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- Precision: 0.9474
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- Recall: 0.9474
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- F1: 0.9474
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- Accuracy: 0.9856
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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: 2000
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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 | 50.0 | 100 | 0.1150 | 0.9 | 0.9474 | 0.9231 | 0.9784 |
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| No log | 100.0 | 200 | 0.1241 | 0.9474 | 0.9474 | 0.9474 | 0.9856 |
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| No log | 150.0 | 300 | 0.1328 | 0.9474 | 0.9474 | 0.9474 | 0.9856 |
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| No log | 200.0 | 400 | 0.1954 | 0.9 | 0.9474 | 0.9231 | 0.9784 |
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| 0.0457 | 250.0 | 500 | 0.1845 | 0.8571 | 0.9474 | 0.9 | 0.9712 |
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| 0.0457 | 300.0 | 600 | 0.0843 | 1.0 | 0.9474 | 0.9730 | 0.9928 |
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| 0.0457 | 350.0 | 700 | 0.0896 | 1.0 | 0.9474 | 0.9730 | 0.9928 |
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| 0.0457 | 400.0 | 800 | 0.0947 | 0.9474 | 0.9474 | 0.9474 | 0.9856 |
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| 0.0457 | 450.0 | 900 | 0.1026 | 0.9474 | 0.9474 | 0.9474 | 0.9856 |
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| 0.0005 | 500.0 | 1000 | 0.1118 | 0.9474 | 0.9474 | 0.9474 | 0.9856 |
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| 0.0005 | 550.0 | 1100 | 0.1196 | 0.9474 | 0.9474 | 0.9474 | 0.9856 |
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| 0.0005 | 600.0 | 1200 | 0.1257 | 0.9474 | 0.9474 | 0.9474 | 0.9856 |
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| 0.0005 | 650.0 | 1300 | 0.1297 | 0.9474 | 0.9474 | 0.9474 | 0.9856 |
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| 0.0005 | 700.0 | 1400 | 0.1334 | 0.9474 | 0.9474 | 0.9474 | 0.9856 |
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| 0.0002 | 750.0 | 1500 | 0.1360 | 0.9474 | 0.9474 | 0.9474 | 0.9856 |
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| 0.0002 | 800.0 | 1600 | 0.1381 | 0.9474 | 0.9474 | 0.9474 | 0.9856 |
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| 0.0002 | 850.0 | 1700 | 0.1389 | 0.9474 | 0.9474 | 0.9474 | 0.9856 |
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| 0.0002 | 900.0 | 1800 | 0.1396 | 0.9474 | 0.9474 | 0.9474 | 0.9856 |
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| 0.0002 | 950.0 | 1900 | 0.1402 | 0.9474 | 0.9474 | 0.9474 | 0.9856 |
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| 0.0002 | 1000.0 | 2000 | 0.1405 | 0.9474 | 0.9474 | 0.9474 | 0.9856 |
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### Framework versions
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- Transformers 4.29.2
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- Pytorch 2.1.0+cu118
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- Datasets 2.14.6
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- Tokenizers 0.13.3
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pytorch_model.bin
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runs/Oct30_15-35-05_b66e54a7c27c/events.out.tfevents.1698680118.b66e54a7c27c.567.0
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