End of training

README.md

@@ -0,0 +1,84 @@
+---
+license: mit
+base_model: SCUT-DLVCLab/lilt-roberta-en-base
+tags:
+- generated_from_trainer
+model-index:
+- name: lilt-en-aadhaar
+  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. -->
+
+# lilt-en-aadhaar
+
+This model is a fine-tuned version of [SCUT-DLVCLab/lilt-roberta-en-base](https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0950
+- Adhaar Number: {'precision': 0.9523809523809523, 'recall': 1.0, 'f1': 0.975609756097561, 'number': 20}
+- Ame: {'precision': 0.9230769230769231, 'recall': 0.9230769230769231, 'f1': 0.9230769230769231, 'number': 13}
+- Ather Name: {'precision': 0.5, 'recall': 0.6666666666666666, 'f1': 0.5714285714285715, 'number': 3}
+- Ather Name Back: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 9}
+- Ather Name Front Top: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4}
+- Ddress Back: {'precision': 0.9032258064516129, 'recall': 0.8235294117647058, 'f1': 0.8615384615384616, 'number': 34}
+- Ddress Front: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 16}
+- Ender: {'precision': 1.0, 'recall': 0.8333333333333334, 'f1': 0.9090909090909091, 'number': 12}
+- Ob: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 13}
+- Obile Number: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 5}
+- Ther: {'precision': 0.898876404494382, 'recall': 0.8791208791208791, 'f1': 0.8888888888888888, 'number': 91}
+- Overall Precision: 0.9256
+- Overall Recall: 0.9045
+- Overall F1: 0.9149
+- Overall Accuracy: 0.9923
+
+## 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: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- training_steps: 2500
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Adhaar Number                                                                             | Ame                                                                                                     | Ather Name                                                                                             | Ather Name Back                                                          | Ather Name Front Top                                      | Ddress Back                                                                                             | Ddress Front                                                                             | Ender                                                                                    | Ob                                                                                      | Obile Number                                                            | Ther                                                                                                    | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:-----------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------:|:---------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| 0.185         | 15.38  | 200  | 0.0832          | {'precision': 0.9090909090909091, 'recall': 1.0, 'f1': 0.9523809523809523, 'number': 20}  | {'precision': 0.9166666666666666, 'recall': 0.8461538461538461, 'f1': 0.8799999999999999, 'number': 13} | {'precision': 0.5, 'recall': 0.6666666666666666, 'f1': 0.5714285714285715, 'number': 3}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 9}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4} | {'precision': 0.8484848484848485, 'recall': 0.8235294117647058, 'f1': 0.8358208955223881, 'number': 34} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 16}                               | {'precision': 1.0, 'recall': 0.8333333333333334, 'f1': 0.9090909090909091, 'number': 12} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 13}                              | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 5}               | {'precision': 0.8539325842696629, 'recall': 0.8351648351648352, 'f1': 0.8444444444444446, 'number': 91} | 0.8940            | 0.8818         | 0.8879     | 0.9884           |
+| 0.0034        | 30.77  | 400  | 0.0860          | {'precision': 0.9047619047619048, 'recall': 0.95, 'f1': 0.9268292682926829, 'number': 20} | {'precision': 0.8461538461538461, 'recall': 0.8461538461538461, 'f1': 0.8461538461538461, 'number': 13} | {'precision': 0.6666666666666666, 'recall': 0.6666666666666666, 'f1': 0.6666666666666666, 'number': 3} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 9}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4} | {'precision': 0.8387096774193549, 'recall': 0.7647058823529411, 'f1': 0.7999999999999999, 'number': 34} | {'precision': 0.9411764705882353, 'recall': 1.0, 'f1': 0.9696969696969697, 'number': 16} | {'precision': 1.0, 'recall': 0.8333333333333334, 'f1': 0.9090909090909091, 'number': 12} | {'precision': 0.9285714285714286, 'recall': 1.0, 'f1': 0.962962962962963, 'number': 13} | {'precision': 1.0, 'recall': 0.8, 'f1': 0.888888888888889, 'number': 5} | {'precision': 0.8444444444444444, 'recall': 0.8351648351648352, 'f1': 0.839779005524862, 'number': 91}  | 0.8796            | 0.8636         | 0.8716     | 0.9877           |
+| 0.0011        | 46.15  | 600  | 0.1305          | {'precision': 0.9047619047619048, 'recall': 0.95, 'f1': 0.9268292682926829, 'number': 20} | {'precision': 0.7692307692307693, 'recall': 0.7692307692307693, 'f1': 0.7692307692307693, 'number': 13} | {'precision': 0.6666666666666666, 'recall': 0.6666666666666666, 'f1': 0.6666666666666666, 'number': 3} | {'precision': 0.9, 'recall': 1.0, 'f1': 0.9473684210526316, 'number': 9} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4} | {'precision': 0.8181818181818182, 'recall': 0.7941176470588235, 'f1': 0.8059701492537314, 'number': 34} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 16}                               | {'precision': 1.0, 'recall': 0.8333333333333334, 'f1': 0.9090909090909091, 'number': 12} | {'precision': 0.9285714285714286, 'recall': 1.0, 'f1': 0.962962962962963, 'number': 13} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 5}               | {'precision': 0.8222222222222222, 'recall': 0.8131868131868132, 'f1': 0.8176795580110496, 'number': 91} | 0.8630            | 0.8591         | 0.8610     | 0.9854           |
+| 0.0013        | 61.54  | 800  | 0.1075          | {'precision': 0.9523809523809523, 'recall': 1.0, 'f1': 0.975609756097561, 'number': 20}   | {'precision': 0.8333333333333334, 'recall': 0.7692307692307693, 'f1': 0.8, 'number': 13}                | {'precision': 0.6666666666666666, 'recall': 0.6666666666666666, 'f1': 0.6666666666666666, 'number': 3} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 9}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4} | {'precision': 0.7878787878787878, 'recall': 0.7647058823529411, 'f1': 0.7761194029850745, 'number': 34} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 16}                               | {'precision': 1.0, 'recall': 0.8333333333333334, 'f1': 0.9090909090909091, 'number': 12} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 13}                              | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 5}               | {'precision': 0.8222222222222222, 'recall': 0.8131868131868132, 'f1': 0.8176795580110496, 'number': 91} | 0.875             | 0.8591         | 0.8670     | 0.9838           |
+| 0.001         | 76.92  | 1000 | 0.1076          | {'precision': 0.9523809523809523, 'recall': 1.0, 'f1': 0.975609756097561, 'number': 20}   | {'precision': 0.8333333333333334, 'recall': 0.7692307692307693, 'f1': 0.8, 'number': 13}                | {'precision': 0.5, 'recall': 0.6666666666666666, 'f1': 0.5714285714285715, 'number': 3}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 9}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4} | {'precision': 0.9032258064516129, 'recall': 0.8235294117647058, 'f1': 0.8615384615384616, 'number': 34} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 16}                               | {'precision': 1.0, 'recall': 0.8333333333333334, 'f1': 0.9090909090909091, 'number': 12} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 13}                              | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 5}               | {'precision': 0.8636363636363636, 'recall': 0.8351648351648352, 'f1': 0.8491620111731844, 'number': 91} | 0.9061            | 0.8773         | 0.8915     | 0.9892           |
+| 0.0003        | 92.31  | 1200 | 0.0856          | {'precision': 0.9523809523809523, 'recall': 1.0, 'f1': 0.975609756097561, 'number': 20}   | {'precision': 0.9230769230769231, 'recall': 0.9230769230769231, 'f1': 0.9230769230769231, 'number': 13} | {'precision': 0.5, 'recall': 0.6666666666666666, 'f1': 0.5714285714285715, 'number': 3}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 9}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4} | {'precision': 0.8125, 'recall': 0.7647058823529411, 'f1': 0.787878787878788, 'number': 34}              | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 16}                               | {'precision': 1.0, 'recall': 0.8333333333333334, 'f1': 0.9090909090909091, 'number': 12} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 13}                              | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 5}               | {'precision': 0.8555555555555555, 'recall': 0.8461538461538461, 'f1': 0.850828729281768, 'number': 91}  | 0.8940            | 0.8818         | 0.8879     | 0.9884           |
+| 0.0001        | 107.69 | 1400 | 0.0950          | {'precision': 0.9523809523809523, 'recall': 1.0, 'f1': 0.975609756097561, 'number': 20}   | {'precision': 0.9230769230769231, 'recall': 0.9230769230769231, 'f1': 0.9230769230769231, 'number': 13} | {'precision': 0.5, 'recall': 0.6666666666666666, 'f1': 0.5714285714285715, 'number': 3}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 9}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4} | {'precision': 0.9032258064516129, 'recall': 0.8235294117647058, 'f1': 0.8615384615384616, 'number': 34} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 16}                               | {'precision': 1.0, 'recall': 0.8333333333333334, 'f1': 0.9090909090909091, 'number': 12} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 13}                              | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 5}               | {'precision': 0.898876404494382, 'recall': 0.8791208791208791, 'f1': 0.8888888888888888, 'number': 91}  | 0.9256            | 0.9045         | 0.9149     | 0.9923           |
+| 0.0001        | 123.08 | 1600 | 0.1075          | {'precision': 0.9047619047619048, 'recall': 0.95, 'f1': 0.9268292682926829, 'number': 20} | {'precision': 0.8461538461538461, 'recall': 0.8461538461538461, 'f1': 0.8461538461538461, 'number': 13} | {'precision': 0.5, 'recall': 0.6666666666666666, 'f1': 0.5714285714285715, 'number': 3}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 9}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4} | {'precision': 0.9032258064516129, 'recall': 0.8235294117647058, 'f1': 0.8615384615384616, 'number': 34} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 16}                               | {'precision': 1.0, 'recall': 0.8333333333333334, 'f1': 0.9090909090909091, 'number': 12} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 13}                              | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 5}               | {'precision': 0.8764044943820225, 'recall': 0.8571428571428571, 'f1': 0.8666666666666666, 'number': 91} | 0.9070            | 0.8864         | 0.8966     | 0.9908           |
+| 0.0002        | 138.46 | 1800 | 0.0919          | {'precision': 0.9047619047619048, 'recall': 0.95, 'f1': 0.9268292682926829, 'number': 20} | {'precision': 0.9230769230769231, 'recall': 0.9230769230769231, 'f1': 0.9230769230769231, 'number': 13} | {'precision': 0.5, 'recall': 0.6666666666666666, 'f1': 0.5714285714285715, 'number': 3}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 9}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4} | {'precision': 0.8484848484848485, 'recall': 0.8235294117647058, 'f1': 0.8358208955223881, 'number': 34} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 16}                               | {'precision': 1.0, 'recall': 0.8333333333333334, 'f1': 0.9090909090909091, 'number': 12} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 13}                              | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 5}               | {'precision': 0.8444444444444444, 'recall': 0.8351648351648352, 'f1': 0.839779005524862, 'number': 91}  | 0.8899            | 0.8818         | 0.8858     | 0.9892           |
+| 0.0001        | 153.85 | 2000 | 0.0953          | {'precision': 0.9047619047619048, 'recall': 0.95, 'f1': 0.9268292682926829, 'number': 20} | {'precision': 0.9230769230769231, 'recall': 0.9230769230769231, 'f1': 0.9230769230769231, 'number': 13} | {'precision': 0.5, 'recall': 0.6666666666666666, 'f1': 0.5714285714285715, 'number': 3}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 9}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4} | {'precision': 0.8484848484848485, 'recall': 0.8235294117647058, 'f1': 0.8358208955223881, 'number': 34} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 16}                               | {'precision': 1.0, 'recall': 0.8333333333333334, 'f1': 0.9090909090909091, 'number': 12} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 13}                              | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 5}               | {'precision': 0.8444444444444444, 'recall': 0.8351648351648352, 'f1': 0.839779005524862, 'number': 91}  | 0.8899            | 0.8818         | 0.8858     | 0.9892           |
+| 0.0001        | 169.23 | 2200 | 0.0974          | {'precision': 0.9047619047619048, 'recall': 0.95, 'f1': 0.9268292682926829, 'number': 20} | {'precision': 0.9230769230769231, 'recall': 0.9230769230769231, 'f1': 0.9230769230769231, 'number': 13} | {'precision': 0.5, 'recall': 0.6666666666666666, 'f1': 0.5714285714285715, 'number': 3}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 9}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4} | {'precision': 0.8484848484848485, 'recall': 0.8235294117647058, 'f1': 0.8358208955223881, 'number': 34} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 16}                               | {'precision': 1.0, 'recall': 0.8333333333333334, 'f1': 0.9090909090909091, 'number': 12} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 13}                              | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 5}               | {'precision': 0.8444444444444444, 'recall': 0.8351648351648352, 'f1': 0.839779005524862, 'number': 91}  | 0.8899            | 0.8818         | 0.8858     | 0.9892           |
+| 0.0           | 184.62 | 2400 | 0.1008          | {'precision': 0.9047619047619048, 'recall': 0.95, 'f1': 0.9268292682926829, 'number': 20} | {'precision': 0.9230769230769231, 'recall': 0.9230769230769231, 'f1': 0.9230769230769231, 'number': 13} | {'precision': 0.5, 'recall': 0.6666666666666666, 'f1': 0.5714285714285715, 'number': 3}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 9}                | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4} | {'precision': 0.8484848484848485, 'recall': 0.8235294117647058, 'f1': 0.8358208955223881, 'number': 34} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 16}                               | {'precision': 1.0, 'recall': 0.8333333333333334, 'f1': 0.9090909090909091, 'number': 12} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 13}                              | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 5}               | {'precision': 0.8444444444444444, 'recall': 0.8351648351648352, 'f1': 0.839779005524862, 'number': 91}  | 0.8899            | 0.8818         | 0.8858     | 0.9892           |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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preprocessor_config.json

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+{
+  "apply_ocr": true,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "LayoutLMv3FeatureExtractor",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "ocr_lang": null,
+  "processor_class": "LayoutLMv3Processor",
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  },
+  "tesseract_config": ""
+}

special_tokens_map.json

@@ -0,0 +1,51 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "cls_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,78 @@
+{
+  "add_prefix_space": true,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
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+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "50264": {
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+      "lstrip": true,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "cls_token_box": [
+    0,
+    0,
+    0,
+    0
+  ],
+  "eos_token": "</s>",
+  "errors": "replace",
+  "mask_token": "<mask>",
+  "model_max_length": 512,
+  "only_label_first_subword": true,
+  "pad_token": "<pad>",
+  "pad_token_box": [
+    0,
+    0,
+    0,
+    0
+  ],
+  "pad_token_label": -100,
+  "processor_class": "LayoutLMv3Processor",
+  "sep_token": "</s>",
+  "sep_token_box": [
+    0,
+    0,
+    0,
+    0
+  ],
+  "tokenizer_class": "LayoutLMv3Tokenizer",
+  "trim_offsets": true,
+  "unk_token": "<unk>"
+}