Added files

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- invoice
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: layoutlmv3-finetuned-invoice
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: Invoice
+      type: invoice
+      args: invoice
+    metrics:
+    - name: Precision
+      type: precision
+      value: 1.0
+    - name: Recall
+      type: recall
+      value: 1.0
+    - name: F1
+      type: f1
+      value: 1.0
+    - name: Accuracy
+      type: accuracy
+      value: 1.0
+---
+
+# LayoutLM-v3 model fine-tuned on invoice dataset
+
+This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the invoice dataset.
+
+We use Microsoft’s LayoutLMv3 trained on Invoice Dataset to predict the Biller Name, Biller Address, Biller post_code, Due_date, GST, Invoice_date, Invoice_number, Subtotal and Total. To use it, simply upload an image or use the example image below. Results will show up in a few seconds.
+
+It achieves the following results on the evaluation set:
+- Loss: 0.0012
+- Precision: 1.0
+- Recall: 1.0
+- F1: 1.0
+- Accuracy: 1.0
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+All the training codes are available from the below GitHub link.
+
+https://github.com/Theivaprakasham/layoutlmv3
+
+
+The model can be evaluated at the HuggingFace Spaces link:
+
+https://huggingface.co/spaces/Theivaprakasham/layoutlmv3_invoice
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- training_steps: 2000
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 2.0   | 100  | 0.0878          | 0.968     | 0.9817 | 0.9748 | 0.9966   |
+| No log        | 4.0   | 200  | 0.0241          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
+| No log        | 6.0   | 300  | 0.0186          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
+| No log        | 8.0   | 400  | 0.0184          | 0.9854    | 0.9574 | 0.9712 | 0.9956   |
+| 0.1308        | 10.0  | 500  | 0.0121          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
+| 0.1308        | 12.0  | 600  | 0.0076          | 0.9939    | 0.9878 | 0.9908 | 0.9987   |
+| 0.1308        | 14.0  | 700  | 0.0047          | 1.0       | 0.9959 | 0.9980 | 0.9996   |
+| 0.1308        | 16.0  | 800  | 0.0036          | 0.9960    | 0.9980 | 0.9970 | 0.9996   |
+| 0.1308        | 18.0  | 900  | 0.0045          | 0.9960    | 0.9980 | 0.9970 | 0.9996   |
+| 0.0069        | 20.0  | 1000 | 0.0043          | 0.9960    | 0.9980 | 0.9970 | 0.9996   |
+| 0.0069        | 22.0  | 1100 | 0.0016          | 1.0       | 1.0    | 1.0    | 1.0      |
+| 0.0069        | 24.0  | 1200 | 0.0015          | 1.0       | 1.0    | 1.0    | 1.0      |
+| 0.0069        | 26.0  | 1300 | 0.0014          | 1.0       | 1.0    | 1.0    | 1.0      |
+| 0.0069        | 28.0  | 1400 | 0.0013          | 1.0       | 1.0    | 1.0    | 1.0      |
+| 0.0026        | 30.0  | 1500 | 0.0012          | 1.0       | 1.0    | 1.0    | 1.0      |
+| 0.0026        | 32.0  | 1600 | 0.0012          | 1.0       | 1.0    | 1.0    | 1.0      |
+| 0.0026        | 34.0  | 1700 | 0.0011          | 1.0       | 1.0    | 1.0    | 1.0      |
+| 0.0026        | 36.0  | 1800 | 0.0011          | 1.0       | 1.0    | 1.0    | 1.0      |
+| 0.0026        | 38.0  | 1900 | 0.0011          | 1.0       | 1.0    | 1.0    | 1.0      |
+| 0.002         | 40.0  | 2000 | 0.0011          | 1.0       | 1.0    | 1.0    | 1.0      |
+
+
+### Framework versions
+
+- Transformers 4.20.0.dev0
+- Pytorch 1.11.0+cu113
+- Datasets 2.2.2
+- Tokenizers 0.12.1

config.json

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+{
+  "_name_or_path": "microsoft/layoutlmv3-base",
+  "architectures": [
+    "LayoutLMv3ForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "coordinate_size": 128,
+  "eos_token_id": 2,
+  "has_relative_attention_bias": true,
+  "has_spatial_attention_bias": true,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "O",
+    "1": "B-ABN",
+    "2": "B-BILLER",
+    "3": "B-BILLER_ADDRESS",
+    "4": "B-BILLER_POST_CODE",
+    "5": "B-DUE_DATE",
+    "6": "B-GST",
+    "7": "B-INVOICE_DATE",
+    "8": "B-INVOICE_NUMBER",
+    "9": "B-SUBTOTAL",
+    "10": "B-TOTAL",
+    "11": "I-BILLER_ADDRESS"
+  },
+  "initializer_range": 0.02,
+  "input_size": 224,
+  "intermediate_size": 3072,
+  "label2id": {
+    "B-ABN": 1,
+    "B-BILLER": 2,
+    "B-BILLER_ADDRESS": 3,
+    "B-BILLER_POST_CODE": 4,
+    "B-DUE_DATE": 5,
+    "B-GST": 6,
+    "B-INVOICE_DATE": 7,
+    "B-INVOICE_NUMBER": 8,
+    "B-SUBTOTAL": 9,
+    "B-TOTAL": 10,
+    "I-BILLER_ADDRESS": 11,
+    "O": 0
+  },
+  "layer_norm_eps": 1e-05,
+  "max_2d_position_embeddings": 1024,
+  "max_position_embeddings": 514,
+  "max_rel_2d_pos": 256,
+  "max_rel_pos": 128,
+  "model_type": "layoutlmv3",
+  "num_attention_heads": 12,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "patch_size": 16,
+  "rel_2d_pos_bins": 64,
+  "rel_pos_bins": 32,
+  "second_input_size": 112,
+  "shape_size": 128,
+  "text_embed": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.20.0.dev0",
+  "type_vocab_size": 1,
+  "visual_embed": true,
+  "vocab_size": 50265
+}

preprocessor_config.json

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+{
+  "apply_ocr": false,
+  "do_normalize": true,
+  "do_resize": true,
+  "feature_extractor_type": "LayoutLMv3FeatureExtractor",
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "ocr_lang": null,
+  "processor_class": "LayoutLMv3Processor",
+  "resample": 2,
+  "size": 224
+}

pytorch_model.bin

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special_tokens_map.json

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tokenizer_config.json

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