End of training

README.md

@@ -0,0 +1,86 @@
+---
+license: mit
+base_model: microsoft/layoutlm-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- blumatix_dataset
+model-index:
+- name: layoutlm-GenText
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# layoutlm-GenText
+
+This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on the blumatix_dataset dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4300
+- At Table Summary: {'precision': 0.7777777777777778, 'recall': 0.875, 'f1': 0.823529411764706, 'number': 8}
+- Aymentinformation: {'precision': 0.7272727272727273, 'recall': 0.6153846153846154, 'f1': 0.6666666666666667, 'number': 13}
+- Eader: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 10}
+- Ineitemtable: {'precision': 0.9090909090909091, 'recall': 1.0, 'f1': 0.9523809523809523, 'number': 10}
+- Nvoicedetails: {'precision': 0.9473684210526315, 'recall': 0.9, 'f1': 0.9230769230769231, 'number': 20}
+- Ogo: {'precision': 0.7, 'recall': 0.7, 'f1': 0.7, 'number': 10}
+- Ontact: {'precision': 0.7222222222222222, 'recall': 0.8125, 'f1': 0.7647058823529411, 'number': 16}
+- Ooter: {'precision': 0.7777777777777778, 'recall': 0.7, 'f1': 0.7368421052631577, 'number': 10}
+- Overall Precision: 0.8247
+- Overall Recall: 0.8247
+- Overall F1: 0.8247
+- Overall Accuracy: 0.8611
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 3e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 15
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | At Table Summary                                                                         | Aymentinformation                                                                                          | Eader                                                                     | Ineitemtable                                                                             | Nvoicedetails                                                                             | Ogo                                                                         | Ontact                                                                                      | Ooter                                                                                     | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:----------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| 1.8986        | 1.0   | 7    | 1.5870          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 8}                                | {'precision': 0.625, 'recall': 0.38461538461538464, 'f1': 0.4761904761904762, 'number': 13}                | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 10}                | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 10}                               | {'precision': 0.16666666666666666, 'recall': 0.25, 'f1': 0.2, 'number': 20}               | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 10}                  | {'precision': 0.27586206896551724, 'recall': 0.5, 'f1': 0.35555555555555557, 'number': 16}  | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 10}                                | 0.2687            | 0.1856         | 0.2195     | 0.4537           |
+| 1.4325        | 2.0   | 14   | 1.1397          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 8}                                | {'precision': 0.42857142857142855, 'recall': 0.46153846153846156, 'f1': 0.4444444444444445, 'number': 13}  | {'precision': 1.0, 'recall': 0.5, 'f1': 0.6666666666666666, 'number': 10} | {'precision': 0.8, 'recall': 0.4, 'f1': 0.5333333333333333, 'number': 10}                | {'precision': 0.44, 'recall': 0.55, 'f1': 0.48888888888888893, 'number': 20}              | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 10}                  | {'precision': 0.375, 'recall': 0.5625, 'f1': 0.45, 'number': 16}                            | {'precision': 0.6666666666666666, 'recall': 0.2, 'f1': 0.30769230769230765, 'number': 10} | 0.4868            | 0.3814         | 0.4277     | 0.5741           |
+| 1.1089        | 3.0   | 21   | 0.8939          | {'precision': 0.4, 'recall': 0.25, 'f1': 0.3076923076923077, 'number': 8}                | {'precision': 0.38461538461538464, 'recall': 0.38461538461538464, 'f1': 0.38461538461538464, 'number': 13} | {'precision': 1.0, 'recall': 0.7, 'f1': 0.8235294117647058, 'number': 10} | {'precision': 0.7777777777777778, 'recall': 0.7, 'f1': 0.7368421052631577, 'number': 10} | {'precision': 0.5454545454545454, 'recall': 0.6, 'f1': 0.5714285714285713, 'number': 20}  | {'precision': 0.625, 'recall': 0.5, 'f1': 0.5555555555555556, 'number': 10} | {'precision': 0.5882352941176471, 'recall': 0.625, 'f1': 0.6060606060606061, 'number': 16}  | {'precision': 0.6666666666666666, 'recall': 0.4, 'f1': 0.5, 'number': 10}                 | 0.5977            | 0.5361         | 0.5652     | 0.6944           |
+| 0.8769        | 4.0   | 28   | 0.7450          | {'precision': 0.5, 'recall': 0.375, 'f1': 0.42857142857142855, 'number': 8}              | {'precision': 0.6363636363636364, 'recall': 0.5384615384615384, 'f1': 0.5833333333333334, 'number': 13}    | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 10}                | {'precision': 0.7777777777777778, 'recall': 0.7, 'f1': 0.7368421052631577, 'number': 10} | {'precision': 0.7894736842105263, 'recall': 0.75, 'f1': 0.7692307692307692, 'number': 20} | {'precision': 0.7, 'recall': 0.7, 'f1': 0.7, 'number': 10}                  | {'precision': 0.7222222222222222, 'recall': 0.8125, 'f1': 0.7647058823529411, 'number': 16} | {'precision': 0.7777777777777778, 'recall': 0.7, 'f1': 0.7368421052631577, 'number': 10}  | 0.75              | 0.7113         | 0.7302     | 0.8056           |
+| 0.7089        | 5.0   | 35   | 0.6354          | {'precision': 1.0, 'recall': 0.75, 'f1': 0.8571428571428571, 'number': 8}                | {'precision': 0.6428571428571429, 'recall': 0.6923076923076923, 'f1': 0.6666666666666666, 'number': 13}    | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 10}                | {'precision': 0.8181818181818182, 'recall': 0.9, 'f1': 0.8571428571428572, 'number': 10} | {'precision': 0.8421052631578947, 'recall': 0.8, 'f1': 0.8205128205128205, 'number': 20}  | {'precision': 0.7, 'recall': 0.7, 'f1': 0.7, 'number': 10}                  | {'precision': 0.7222222222222222, 'recall': 0.8125, 'f1': 0.7647058823529411, 'number': 16} | {'precision': 0.7777777777777778, 'recall': 0.7, 'f1': 0.7368421052631577, 'number': 10}  | 0.7938            | 0.7938         | 0.7938     | 0.8426           |
+| 0.6253        | 6.0   | 42   | 0.5627          | {'precision': 1.0, 'recall': 0.875, 'f1': 0.9333333333333333, 'number': 8}               | {'precision': 0.6428571428571429, 'recall': 0.6923076923076923, 'f1': 0.6666666666666666, 'number': 13}    | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 10}                | {'precision': 0.9, 'recall': 0.9, 'f1': 0.9, 'number': 10}                               | {'precision': 0.8947368421052632, 'recall': 0.85, 'f1': 0.8717948717948718, 'number': 20} | {'precision': 0.7, 'recall': 0.7, 'f1': 0.7, 'number': 10}                  | {'precision': 0.7058823529411765, 'recall': 0.75, 'f1': 0.7272727272727272, 'number': 16}   | {'precision': 0.7, 'recall': 0.7, 'f1': 0.7, 'number': 10}                                | 0.8041            | 0.8041         | 0.8041     | 0.8519           |
+| 0.5632        | 7.0   | 49   | 0.5253          | {'precision': 1.0, 'recall': 0.875, 'f1': 0.9333333333333333, 'number': 8}               | {'precision': 0.75, 'recall': 0.6923076923076923, 'f1': 0.7199999999999999, 'number': 13}                  | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 10}                | {'precision': 0.8181818181818182, 'recall': 0.9, 'f1': 0.8571428571428572, 'number': 10} | {'precision': 0.8, 'recall': 0.8, 'f1': 0.8000000000000002, 'number': 20}                 | {'precision': 0.7, 'recall': 0.7, 'f1': 0.7, 'number': 10}                  | {'precision': 0.7222222222222222, 'recall': 0.8125, 'f1': 0.7647058823529411, 'number': 16} | {'precision': 0.75, 'recall': 0.6, 'f1': 0.6666666666666665, 'number': 10}                | 0.8021            | 0.7938         | 0.7979     | 0.8426           |
+| 0.5003        | 8.0   | 56   | 0.4927          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 8}                                | {'precision': 0.7142857142857143, 'recall': 0.7692307692307693, 'f1': 0.7407407407407408, 'number': 13}    | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 10}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 10}                               | {'precision': 0.9473684210526315, 'recall': 0.9, 'f1': 0.9230769230769231, 'number': 20}  | {'precision': 0.7, 'recall': 0.7, 'f1': 0.7, 'number': 10}                  | {'precision': 0.7222222222222222, 'recall': 0.8125, 'f1': 0.7647058823529411, 'number': 16} | {'precision': 0.7777777777777778, 'recall': 0.7, 'f1': 0.7368421052631577, 'number': 10}  | 0.8469            | 0.8557         | 0.8513     | 0.8796           |
+| 0.4502        | 9.0   | 63   | 0.4682          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 8}                                | {'precision': 0.7142857142857143, 'recall': 0.7692307692307693, 'f1': 0.7407407407407408, 'number': 13}    | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 10}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 10}                               | {'precision': 0.9473684210526315, 'recall': 0.9, 'f1': 0.9230769230769231, 'number': 20}  | {'precision': 0.7, 'recall': 0.7, 'f1': 0.7, 'number': 10}                  | {'precision': 0.7222222222222222, 'recall': 0.8125, 'f1': 0.7647058823529411, 'number': 16} | {'precision': 0.7777777777777778, 'recall': 0.7, 'f1': 0.7368421052631577, 'number': 10}  | 0.8469            | 0.8557         | 0.8513     | 0.8796           |
+| 0.4891        | 10.0  | 70   | 0.4630          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 8}                                | {'precision': 0.6923076923076923, 'recall': 0.6923076923076923, 'f1': 0.6923076923076923, 'number': 13}    | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 10}                | {'precision': 0.9090909090909091, 'recall': 1.0, 'f1': 0.9523809523809523, 'number': 10} | {'precision': 0.9, 'recall': 0.9, 'f1': 0.9, 'number': 20}                                | {'precision': 0.7, 'recall': 0.7, 'f1': 0.7, 'number': 10}                  | {'precision': 0.7058823529411765, 'recall': 0.75, 'f1': 0.7272727272727272, 'number': 16}   | {'precision': 0.75, 'recall': 0.6, 'f1': 0.6666666666666665, 'number': 10}                | 0.8247            | 0.8247         | 0.8247     | 0.8611           |
+| 0.4707        | 11.0  | 77   | 0.4498          | {'precision': 0.8888888888888888, 'recall': 1.0, 'f1': 0.9411764705882353, 'number': 8}  | {'precision': 0.75, 'recall': 0.6923076923076923, 'f1': 0.7199999999999999, 'number': 13}                  | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 10}                | {'precision': 0.9090909090909091, 'recall': 1.0, 'f1': 0.9523809523809523, 'number': 10} | {'precision': 0.9473684210526315, 'recall': 0.9, 'f1': 0.9230769230769231, 'number': 20}  | {'precision': 0.7, 'recall': 0.7, 'f1': 0.7, 'number': 10}                  | {'precision': 0.7222222222222222, 'recall': 0.8125, 'f1': 0.7647058823529411, 'number': 16} | {'precision': 0.7777777777777778, 'recall': 0.7, 'f1': 0.7368421052631577, 'number': 10}  | 0.8367            | 0.8454         | 0.8410     | 0.8704           |
+| 0.3707        | 12.0  | 84   | 0.4455          | {'precision': 0.7777777777777778, 'recall': 0.875, 'f1': 0.823529411764706, 'number': 8} | {'precision': 0.7272727272727273, 'recall': 0.6153846153846154, 'f1': 0.6666666666666667, 'number': 13}    | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 10}                | {'precision': 0.9090909090909091, 'recall': 1.0, 'f1': 0.9523809523809523, 'number': 10} | {'precision': 0.9473684210526315, 'recall': 0.9, 'f1': 0.9230769230769231, 'number': 20}  | {'precision': 0.7, 'recall': 0.7, 'f1': 0.7, 'number': 10}                  | {'precision': 0.7222222222222222, 'recall': 0.8125, 'f1': 0.7647058823529411, 'number': 16} | {'precision': 0.7777777777777778, 'recall': 0.7, 'f1': 0.7368421052631577, 'number': 10}  | 0.8247            | 0.8247         | 0.8247     | 0.8611           |
+| 0.3966        | 13.0  | 91   | 0.4352          | {'precision': 0.7777777777777778, 'recall': 0.875, 'f1': 0.823529411764706, 'number': 8} | {'precision': 0.6363636363636364, 'recall': 0.5384615384615384, 'f1': 0.5833333333333334, 'number': 13}    | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 10}                | {'precision': 0.9090909090909091, 'recall': 1.0, 'f1': 0.9523809523809523, 'number': 10} | {'precision': 0.9473684210526315, 'recall': 0.9, 'f1': 0.9230769230769231, 'number': 20}  | {'precision': 0.7, 'recall': 0.7, 'f1': 0.7, 'number': 10}                  | {'precision': 0.7058823529411765, 'recall': 0.75, 'f1': 0.7272727272727272, 'number': 16}   | {'precision': 0.7777777777777778, 'recall': 0.7, 'f1': 0.7368421052631577, 'number': 10}  | 0.8125            | 0.8041         | 0.8083     | 0.8519           |
+| 0.3643        | 14.0  | 98   | 0.4309          | {'precision': 0.875, 'recall': 0.875, 'f1': 0.875, 'number': 8}                          | {'precision': 0.6923076923076923, 'recall': 0.6923076923076923, 'f1': 0.6923076923076923, 'number': 13}    | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 10}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 10}                               | {'precision': 0.9473684210526315, 'recall': 0.9, 'f1': 0.9230769230769231, 'number': 20}  | {'precision': 0.7, 'recall': 0.7, 'f1': 0.7, 'number': 10}                  | {'precision': 0.7222222222222222, 'recall': 0.8125, 'f1': 0.7647058823529411, 'number': 16} | {'precision': 0.7777777777777778, 'recall': 0.7, 'f1': 0.7368421052631577, 'number': 10}  | 0.8351            | 0.8351         | 0.8351     | 0.8704           |
+| 0.3919        | 15.0  | 105  | 0.4300          | {'precision': 0.7777777777777778, 'recall': 0.875, 'f1': 0.823529411764706, 'number': 8} | {'precision': 0.7272727272727273, 'recall': 0.6153846153846154, 'f1': 0.6666666666666667, 'number': 13}    | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 10}                | {'precision': 0.9090909090909091, 'recall': 1.0, 'f1': 0.9523809523809523, 'number': 10} | {'precision': 0.9473684210526315, 'recall': 0.9, 'f1': 0.9230769230769231, 'number': 20}  | {'precision': 0.7, 'recall': 0.7, 'f1': 0.7, 'number': 10}                  | {'precision': 0.7222222222222222, 'recall': 0.8125, 'f1': 0.7647058823529411, 'number': 16} | {'precision': 0.7777777777777778, 'recall': 0.7, 'f1': 0.7368421052631577, 'number': 10}  | 0.8247            | 0.8247         | 0.8247     | 0.8611           |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

logs/events.out.tfevents.1710948155.DESKTOP-HA84SVN.2345998.0

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preprocessor_config.json

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special_tokens_map.json

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+    "rstrip": false,
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tokenizer_config.json

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+}