End of training

README.md

@@ -0,0 +1,76 @@
+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- funsd-layoutlmv3
+model-index:
+- name: lilt-en-funsd
+  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-funsd
+
+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 funsd-layoutlmv3 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.7343
+- Answer: {'precision': 0.865979381443299, 'recall': 0.9253365973072215, 'f1': 0.8946745562130176, 'number': 817}
+- Header: {'precision': 0.6442307692307693, 'recall': 0.5630252100840336, 'f1': 0.600896860986547, 'number': 119}
+- Question: {'precision': 0.8937329700272479, 'recall': 0.9136490250696379, 'f1': 0.9035812672176309, 'number': 1077}
+- Overall Precision: 0.8696
+- Overall Recall: 0.8977
+- Overall F1: 0.8834
+- Overall Accuracy: 0.8048
+
+## 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
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Answer                                                                                                   | Header                                                                                                    | Question                                                                                                  | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| 0.4108        | 10.53  | 200  | 0.9777          | {'precision': 0.8268590455049944, 'recall': 0.9118727050183598, 'f1': 0.8672875436554133, 'number': 817} | {'precision': 0.6464646464646465, 'recall': 0.5378151260504201, 'f1': 0.5871559633027523, 'number': 119}  | {'precision': 0.8931860036832413, 'recall': 0.9006499535747446, 'f1': 0.8969024503005086, 'number': 1077} | 0.8528            | 0.8838         | 0.8680     | 0.8028           |
+| 0.0416        | 21.05  | 400  | 1.3626          | {'precision': 0.8482446206115515, 'recall': 0.9167686658506732, 'f1': 0.8811764705882352, 'number': 817} | {'precision': 0.5266666666666666, 'recall': 0.6638655462184874, 'f1': 0.5873605947955389, 'number': 119}  | {'precision': 0.891566265060241, 'recall': 0.89322191272052, 'f1': 0.8923933209647495, 'number': 1077}    | 0.8475            | 0.8892         | 0.8679     | 0.8033           |
+| 0.017         | 31.58  | 600  | 1.4784          | {'precision': 0.8646341463414634, 'recall': 0.8678090575275398, 'f1': 0.8662186927306048, 'number': 817} | {'precision': 0.6486486486486487, 'recall': 0.6050420168067226, 'f1': 0.6260869565217391, 'number': 119}  | {'precision': 0.8519148936170213, 'recall': 0.9294336118848654, 'f1': 0.8889875666074601, 'number': 1077} | 0.8462            | 0.8852         | 0.8653     | 0.7964           |
+| 0.0098        | 42.11  | 800  | 1.4397          | {'precision': 0.8267543859649122, 'recall': 0.9228886168910648, 'f1': 0.8721804511278195, 'number': 817} | {'precision': 0.5865384615384616, 'recall': 0.5126050420168067, 'f1': 0.5470852017937219, 'number': 119}  | {'precision': 0.8928247048138056, 'recall': 0.9127205199628597, 'f1': 0.9026629935720845, 'number': 1077} | 0.8493            | 0.8932         | 0.8707     | 0.8077           |
+| 0.004         | 52.63  | 1000 | 1.5432          | {'precision': 0.8721893491124261, 'recall': 0.9020807833537332, 'f1': 0.8868832731648616, 'number': 817} | {'precision': 0.5681818181818182, 'recall': 0.6302521008403361, 'f1': 0.597609561752988, 'number': 119}   | {'precision': 0.8956999085086916, 'recall': 0.9090064995357474, 'f1': 0.9023041474654377, 'number': 1077} | 0.8652            | 0.8897         | 0.8773     | 0.8162           |
+| 0.0025        | 63.16  | 1200 | 1.6970          | {'precision': 0.8733727810650888, 'recall': 0.9033047735618115, 'f1': 0.888086642599278, 'number': 817}  | {'precision': 0.7215189873417721, 'recall': 0.4789915966386555, 'f1': 0.5757575757575758, 'number': 119}  | {'precision': 0.8804251550044287, 'recall': 0.9229340761374187, 'f1': 0.901178603807797, 'number': 1077}  | 0.8714            | 0.8887         | 0.8800     | 0.7970           |
+| 0.0012        | 73.68  | 1400 | 1.6351          | {'precision': 0.8643274853801169, 'recall': 0.9045287637698899, 'f1': 0.8839712918660287, 'number': 817} | {'precision': 0.6115702479338843, 'recall': 0.6218487394957983, 'f1': 0.6166666666666667, 'number': 119}  | {'precision': 0.8899821109123435, 'recall': 0.9238625812441968, 'f1': 0.9066059225512528, 'number': 1077} | 0.8634            | 0.8982         | 0.8804     | 0.8059           |
+| 0.0006        | 84.21  | 1600 | 1.5729          | {'precision': 0.8616279069767442, 'recall': 0.9069767441860465, 'f1': 0.8837209302325582, 'number': 817} | {'precision': 0.6973684210526315, 'recall': 0.44537815126050423, 'f1': 0.5435897435897435, 'number': 119} | {'precision': 0.878868258178603, 'recall': 0.9229340761374187, 'f1': 0.9003623188405797, 'number': 1077}  | 0.8650            | 0.8882         | 0.8765     | 0.8149           |
+| 0.0008        | 94.74  | 1800 | 1.8110          | {'precision': 0.8455467869222097, 'recall': 0.9179926560587516, 'f1': 0.880281690140845, 'number': 817}  | {'precision': 0.5522388059701493, 'recall': 0.6218487394957983, 'f1': 0.5849802371541502, 'number': 119}  | {'precision': 0.9101851851851852, 'recall': 0.9127205199628597, 'f1': 0.9114510894761243, 'number': 1077} | 0.8601            | 0.8977         | 0.8785     | 0.7979           |
+| 0.0003        | 105.26 | 2000 | 1.7278          | {'precision': 0.8635321100917431, 'recall': 0.9216646266829865, 'f1': 0.8916518650088809, 'number': 817} | {'precision': 0.591304347826087, 'recall': 0.5714285714285714, 'f1': 0.5811965811965812, 'number': 119}   | {'precision': 0.8986301369863013, 'recall': 0.9136490250696379, 'f1': 0.9060773480662985, 'number': 1077} | 0.8670            | 0.8967         | 0.8816     | 0.8005           |
+| 0.0004        | 115.79 | 2200 | 1.7088          | {'precision': 0.8802816901408451, 'recall': 0.9179926560587516, 'f1': 0.8987417615338527, 'number': 817} | {'precision': 0.6120689655172413, 'recall': 0.5966386554621849, 'f1': 0.6042553191489363, 'number': 119}  | {'precision': 0.8869801084990958, 'recall': 0.9108635097493036, 'f1': 0.8987631699496106, 'number': 1077} | 0.8689            | 0.8952         | 0.8818     | 0.8051           |
+| 0.0003        | 126.32 | 2400 | 1.7343          | {'precision': 0.865979381443299, 'recall': 0.9253365973072215, 'f1': 0.8946745562130176, 'number': 817}  | {'precision': 0.6442307692307693, 'recall': 0.5630252100840336, 'f1': 0.600896860986547, 'number': 119}   | {'precision': 0.8937329700272479, 'recall': 0.9136490250696379, 'f1': 0.9035812672176309, 'number': 1077} | 0.8696            | 0.8977         | 0.8834     | 0.8048           |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 1.13.1+cu117
+- Datasets 2.11.0
+- Tokenizers 0.13.3

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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
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+  "tesseract_config": ""
+}

special_tokens_map.json

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+{
+  "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
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+  "mask_token": {
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+    "lstrip": true,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
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+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
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+  "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

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+{
+  "add_prefix_space": true,
+  "bos_token": {
+    "__type": "AddedToken",
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
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+  "clean_up_tokenization_spaces": true,
+  "cls_token": {
+    "__type": "AddedToken",
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
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+  "cls_token_box": [
+    0,
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+  "eos_token": {
+    "__type": "AddedToken",
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
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+  "errors": "replace",
+  "mask_token": {
+    "__type": "AddedToken",
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
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+  "model_max_length": 512,
+  "only_label_first_subword": true,
+  "pad_token": {
+    "__type": "AddedToken",
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
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+  "pad_token_label": -100,
+  "processor_class": "LayoutLMv3Processor",
+  "sep_token": {
+    "__type": "AddedToken",
+    "content": "</s>",
+    "lstrip": false,
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+    "rstrip": false,
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+    "__type": "AddedToken",
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  }
+}