End of training

README.md

@@ -0,0 +1,77 @@
+---
+license: mit
+base_model: SCUT-DLVCLab/lilt-roberta-en-base
+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: 1.7029
+- Answer: {'precision': 0.8619489559164734, 'recall': 0.9094247246022031, 'f1': 0.8850506253722453, 'number': 817}
+- Header: {'precision': 0.648936170212766, 'recall': 0.5126050420168067, 'f1': 0.5727699530516431, 'number': 119}
+- Question: {'precision': 0.8972046889089269, 'recall': 0.9238625812441968, 'f1': 0.9103385178408051, 'number': 1077}
+- Overall Precision: 0.8712
+- Overall Recall: 0.8937
+- Overall F1: 0.8823
+- Overall Accuracy: 0.8004
+
+## 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| 0.4178        | 10.53  | 200  | 1.1592          | {'precision': 0.8244444444444444, 'recall': 0.9082007343941249, 'f1': 0.8642981945253349, 'number': 817} | {'precision': 0.62, 'recall': 0.5210084033613446, 'f1': 0.5662100456621004, 'number': 119}                | {'precision': 0.874561403508772, 'recall': 0.9257195914577531, 'f1': 0.8994136220117277, 'number': 1077}  | 0.8416            | 0.8947         | 0.8673     | 0.7757           |
+| 0.0458        | 21.05  | 400  | 1.3058          | {'precision': 0.8473988439306358, 'recall': 0.8971848225214198, 'f1': 0.8715814506539833, 'number': 817} | {'precision': 0.5462184873949579, 'recall': 0.5462184873949579, 'f1': 0.5462184873949579, 'number': 119}  | {'precision': 0.8808243727598566, 'recall': 0.9127205199628597, 'f1': 0.8964888280893752, 'number': 1077} | 0.8481            | 0.8847         | 0.8660     | 0.7946           |
+| 0.0135        | 31.58  | 600  | 1.6170          | {'precision': 0.855188141391106, 'recall': 0.9179926560587516, 'f1': 0.885478158205431, 'number': 817}   | {'precision': 0.5737704918032787, 'recall': 0.5882352941176471, 'f1': 0.5809128630705394, 'number': 119}  | {'precision': 0.8915223336371924, 'recall': 0.9080779944289693, 'f1': 0.8997240110395583, 'number': 1077} | 0.8578            | 0.8932         | 0.8752     | 0.7978           |
+| 0.0081        | 42.11  | 800  | 1.3449          | {'precision': 0.8650602409638555, 'recall': 0.8788249694002448, 'f1': 0.8718882817243473, 'number': 817} | {'precision': 0.6476190476190476, 'recall': 0.5714285714285714, 'f1': 0.6071428571428571, 'number': 119}  | {'precision': 0.8675324675324675, 'recall': 0.9303621169916435, 'f1': 0.8978494623655914, 'number': 1077} | 0.8555            | 0.8882         | 0.8716     | 0.8073           |
+| 0.0048        | 52.63  | 1000 | 1.4197          | {'precision': 0.8709288299155609, 'recall': 0.8837209302325582, 'f1': 0.8772782503037667, 'number': 817} | {'precision': 0.5925925925925926, 'recall': 0.5378151260504201, 'f1': 0.5638766519823789, 'number': 119}  | {'precision': 0.8701298701298701, 'recall': 0.9331476323119777, 'f1': 0.9005376344086022, 'number': 1077} | 0.8561            | 0.8897         | 0.8726     | 0.8155           |
+| 0.0021        | 63.16  | 1200 | 1.5708          | {'precision': 0.8366666666666667, 'recall': 0.9216646266829865, 'f1': 0.8771112405358183, 'number': 817} | {'precision': 0.6590909090909091, 'recall': 0.48739495798319327, 'f1': 0.5603864734299517, 'number': 119} | {'precision': 0.8841628959276018, 'recall': 0.9071494893221913, 'f1': 0.8955087076076994, 'number': 1077} | 0.8543            | 0.8882         | 0.8709     | 0.8014           |
+| 0.0019        | 73.68  | 1400 | 1.5995          | {'precision': 0.8174946004319654, 'recall': 0.9265605875152999, 'f1': 0.8686173264486519, 'number': 817} | {'precision': 0.5892857142857143, 'recall': 0.5546218487394958, 'f1': 0.5714285714285715, 'number': 119}  | {'precision': 0.8880800727934486, 'recall': 0.9062209842154132, 'f1': 0.8970588235294117, 'number': 1077} | 0.8418            | 0.8937         | 0.8670     | 0.8108           |
+| 0.0015        | 84.21  | 1600 | 1.6443          | {'precision': 0.8770883054892601, 'recall': 0.8996328029375765, 'f1': 0.8882175226586103, 'number': 817} | {'precision': 0.5945945945945946, 'recall': 0.5546218487394958, 'f1': 0.5739130434782609, 'number': 119}  | {'precision': 0.8947368421052632, 'recall': 0.9155060352831941, 'f1': 0.9050022946305646, 'number': 1077} | 0.8713            | 0.8877         | 0.8794     | 0.8002           |
+| 0.0011        | 94.74  | 1800 | 1.6845          | {'precision': 0.8622685185185185, 'recall': 0.9118727050183598, 'f1': 0.8863771564544913, 'number': 817} | {'precision': 0.6444444444444445, 'recall': 0.48739495798319327, 'f1': 0.5550239234449761, 'number': 119} | {'precision': 0.8973660308810173, 'recall': 0.9173630454967502, 'f1': 0.9072543617998163, 'number': 1077} | 0.8715            | 0.8897         | 0.8805     | 0.7996           |
+| 0.0003        | 105.26 | 2000 | 1.6754          | {'precision': 0.8582949308755761, 'recall': 0.9118727050183598, 'f1': 0.8842729970326408, 'number': 817} | {'precision': 0.5961538461538461, 'recall': 0.5210084033613446, 'f1': 0.5560538116591929, 'number': 119}  | {'precision': 0.9006381039197813, 'recall': 0.9173630454967502, 'f1': 0.9089236430542779, 'number': 1077} | 0.8676            | 0.8917         | 0.8795     | 0.8034           |
+| 0.0003        | 115.79 | 2200 | 1.6803          | {'precision': 0.8733727810650888, 'recall': 0.9033047735618115, 'f1': 0.888086642599278, 'number': 817}  | {'precision': 0.6116504854368932, 'recall': 0.5294117647058824, 'f1': 0.5675675675675675, 'number': 119}  | {'precision': 0.8938294010889292, 'recall': 0.914577530176416, 'f1': 0.9040844424047729, 'number': 1077}  | 0.8712            | 0.8872         | 0.8792     | 0.8014           |
+| 0.0004        | 126.32 | 2400 | 1.7029          | {'precision': 0.8619489559164734, 'recall': 0.9094247246022031, 'f1': 0.8850506253722453, 'number': 817} | {'precision': 0.648936170212766, 'recall': 0.5126050420168067, 'f1': 0.5727699530516431, 'number': 119}   | {'precision': 0.8972046889089269, 'recall': 0.9238625812441968, 'f1': 0.9103385178408051, 'number': 1077} | 0.8712            | 0.8937         | 0.8823     | 0.8004           |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.1

preprocessor_config.json

@@ -0,0 +1,26 @@
+{
+  "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
+    },
+    "3": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "50264": {
+      "content": "<mask>",
+      "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>"
+}