End of training

README.md

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+---
+tags:
+- generated_from_trainer
+model-index:
+- name: layoutlm-custom
+  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-custom
+
+This model was trained from scratch on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1583
+-  Noise: {'precision': 0.8818897637795275, 'recall': 0.8736349453978159, 'f1': 0.8777429467084641, 'number': 641}
+-  Signal: {'precision': 0.861198738170347, 'recall': 0.853125, 'f1': 0.8571428571428572, 'number': 640}
+- Overall Precision: 0.8716
+- Overall Recall: 0.8634
+- Overall F1: 0.8675
+- Overall Accuracy: 0.9656
+
+## 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: 8
+- 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 |  Noise                                                                                                   |  Signal                                                                                         | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| 0.3882        | 1.0   | 18   | 0.2617          | {'precision': 0.6654804270462633, 'recall': 0.5834633385335414, 'f1': 0.6217788861180383, 'number': 641} | {'precision': 0.6149732620320856, 'recall': 0.5390625, 'f1': 0.5745212323064114, 'number': 640} | 0.6402            | 0.5613         | 0.5982     | 0.8986           |
+| 0.1694        | 2.0   | 36   | 0.1752          | {'precision': 0.7387820512820513, 'recall': 0.719188767550702, 'f1': 0.7288537549407115, 'number': 641}  | {'precision': 0.709470304975923, 'recall': 0.690625, 'f1': 0.6999208234362629, 'number': 640}   | 0.7241            | 0.7049         | 0.7144     | 0.9296           |
+| 0.1039        | 3.0   | 54   | 0.1356          | {'precision': 0.7865168539325843, 'recall': 0.7644305772230889, 'f1': 0.7753164556962026, 'number': 641} | {'precision': 0.77491961414791, 'recall': 0.753125, 'f1': 0.7638668779714739, 'number': 640}    | 0.7807            | 0.7588         | 0.7696     | 0.9439           |
+| 0.064         | 4.0   | 72   | 0.1342          | {'precision': 0.8220472440944881, 'recall': 0.8143525741029641, 'f1': 0.8181818181818181, 'number': 641} | {'precision': 0.8028391167192429, 'recall': 0.7953125, 'f1': 0.7990580847723705, 'number': 640} | 0.8125            | 0.8048         | 0.8086     | 0.9522           |
+| 0.0433        | 5.0   | 90   | 0.1241          | {'precision': 0.8544303797468354, 'recall': 0.8424336973478939, 'f1': 0.8483896307934014, 'number': 641} | {'precision': 0.8320126782884311, 'recall': 0.8203125, 'f1': 0.8261211644374509, 'number': 640} | 0.8432            | 0.8314         | 0.8373     | 0.9601           |
+| 0.0293        | 6.0   | 108  | 0.1274          | {'precision': 0.8650793650793651, 'recall': 0.8502340093603744, 'f1': 0.8575924468922109, 'number': 641} | {'precision': 0.8378378378378378, 'recall': 0.8234375, 'f1': 0.830575256107171, 'number': 640}  | 0.8515            | 0.8368         | 0.8441     | 0.9617           |
+| 0.0199        | 7.0   | 126  | 0.1372          | {'precision': 0.8722397476340694, 'recall': 0.8627145085803433, 'f1': 0.8674509803921568, 'number': 641} | {'precision': 0.8530805687203792, 'recall': 0.84375, 'f1': 0.8483896307934015, 'number': 640}   | 0.8627            | 0.8532         | 0.8579     | 0.9640           |
+| 0.0139        | 8.0   | 144  | 0.1386          | {'precision': 0.8839427662957074, 'recall': 0.8673946957878315, 'f1': 0.8755905511811023, 'number': 641} | {'precision': 0.856687898089172, 'recall': 0.840625, 'f1': 0.8485804416403785, 'number': 640}   | 0.8703            | 0.8540         | 0.8621     | 0.9656           |
+| 0.0126        | 9.0   | 162  | 0.1467          | {'precision': 0.8829113924050633, 'recall': 0.8705148205928237, 'f1': 0.8766692851531814, 'number': 641} | {'precision': 0.8541996830427893, 'recall': 0.8421875, 'f1': 0.848151062155783, 'number': 640}  | 0.8686            | 0.8564         | 0.8624     | 0.9654           |
+| 0.0114        | 10.0  | 180  | 0.1531          | {'precision': 0.8694968553459119, 'recall': 0.8627145085803433, 'f1': 0.8660924040720438, 'number': 641} | {'precision': 0.8472440944881889, 'recall': 0.840625, 'f1': 0.8439215686274509, 'number': 640}  | 0.8584            | 0.8517         | 0.8550     | 0.9631           |
+| 0.0099        | 11.0  | 198  | 0.1581          | {'precision': 0.8703125, 'recall': 0.8689547581903276, 'f1': 0.8696330991412958, 'number': 641}          | {'precision': 0.8450704225352113, 'recall': 0.84375, 'f1': 0.8444096950742768, 'number': 640}   | 0.8577            | 0.8564         | 0.8570     | 0.9634           |
+| 0.0064        | 12.0  | 216  | 0.1543          | {'precision': 0.8866141732283465, 'recall': 0.8783151326053042, 'f1': 0.8824451410658307, 'number': 641} | {'precision': 0.8643533123028391, 'recall': 0.85625, 'f1': 0.8602825745682888, 'number': 640}   | 0.8755            | 0.8673         | 0.8714     | 0.9659           |
+| 0.0059        | 13.0  | 234  | 0.1628          | {'precision': 0.8732394366197183, 'recall': 0.8705148205928237, 'f1': 0.871875, 'number': 641}           | {'precision': 0.8526645768025078, 'recall': 0.85, 'f1': 0.8513302034428795, 'number': 640}      | 0.8630            | 0.8603         | 0.8616     | 0.9645           |
+| 0.0056        | 14.0  | 252  | 0.1587          | {'precision': 0.878740157480315, 'recall': 0.8705148205928237, 'f1': 0.8746081504702194, 'number': 641}  | {'precision': 0.8580441640378549, 'recall': 0.85, 'f1': 0.8540031397174254, 'number': 640}      | 0.8684            | 0.8603         | 0.8643     | 0.9651           |
+| 0.005         | 15.0  | 270  | 0.1583          | {'precision': 0.8818897637795275, 'recall': 0.8736349453978159, 'f1': 0.8777429467084641, 'number': 641} | {'precision': 0.861198738170347, 'recall': 0.853125, 'f1': 0.8571428571428572, 'number': 640}   | 0.8716            | 0.8634         | 0.8675     | 0.9656           |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0

config.json

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+{
+  "_name_or_path": "uttam333/layoutlm-funsd",
+  "architectures": [
+    "LayoutLMForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "noise",
+    "1": "signal"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "noise": 0,
+    "signal": 1
+  },
+  "layer_norm_eps": 1e-12,
+  "max_2d_position_embeddings": 1024,
+  "max_position_embeddings": 512,
+  "model_type": "layoutlm",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.36.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

logs/events.out.tfevents.1704789383.7150262428ca.598.1

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model.safetensors

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preprocessor_config.json

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+{
+  "apply_ocr": false,
+  "do_resize": true,
+  "feature_extractor_type": "LayoutLMv2FeatureExtractor",
+  "image_processor_type": "LayoutLMv2ImageProcessor",
+  "ocr_lang": null,
+  "processor_class": "LayoutLMv2Processor",
+  "resample": 2,
+  "size": {
+    "height": 224,
+    "width": 224
+  },
+  "tesseract_config": ""
+}

special_tokens_map.json

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+{
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "[MASK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "[PAD]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "[SEP]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+    "102": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+  },
+  "additional_special_tokens": [],
+  "apply_ocr": false,
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "cls_token_box": [
+    0,
+    0,
+    0,
+    0
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+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "max_length": 512,
+  "model_max_length": 512,
+  "never_split": null,
+  "only_label_first_subword": true,
+  "pad_to_multiple_of": null,
+  "pad_token": "[PAD]",
+  "pad_token_box": [
+    0,
+    0,
+    0,
+    0
+  ],
+  "pad_token_label": -100,
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "processor_class": "LayoutLMv2Processor",
+  "sep_token": "[SEP]",
+  "sep_token_box": [
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+    1000,
+    1000,
+    1000
+  ],
+  "stride": 0,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "LayoutLMv2Tokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}

training_args.bin

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