End of training

README.md

@@ -0,0 +1,84 @@
+---
+license: mit
+base_model: microsoft/layoutlm-base-uncased
+tags:
+- generated_from_trainer
+model-index:
+- name: layoutlm-cord
+  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-cord
+
+This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- eval_loss: 0.1624
+- eval_enu.cnt: {'precision': 0.9861111111111112, 'recall': 0.9681818181818181, 'f1': 0.9770642201834862, 'number': 220}
+- eval_enu.discountprice: {'precision': 0.6666666666666666, 'recall': 0.6, 'f1': 0.631578947368421, 'number': 10}
+- eval_enu.etc: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3}
+- eval_enu.itemsubtotal: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 6}
+- eval_enu.nm: {'precision': 0.9525691699604744, 'recall': 0.9601593625498008, 'f1': 0.9563492063492064, 'number': 251}
+- eval_enu.num: {'precision': 0.9090909090909091, 'recall': 0.9090909090909091, 'f1': 0.9090909090909091, 'number': 11}
+- eval_enu.price: {'precision': 0.9568627450980393, 'recall': 0.991869918699187, 'f1': 0.9740518962075848, 'number': 246}
+- eval_enu.sub.cnt: {'precision': 0.85, 'recall': 1.0, 'f1': 0.9189189189189189, 'number': 17}
+- eval_enu.sub.nm: {'precision': 0.8285714285714286, 'recall': 0.9354838709677419, 'f1': 0.8787878787878788, 'number': 31}
+- eval_enu.sub.price: {'precision': 1.0, 'recall': 0.95, 'f1': 0.9743589743589743, 'number': 20}
+- eval_enu.unitprice: {'precision': 0.984375, 'recall': 0.9402985074626866, 'f1': 0.9618320610687023, 'number': 67}
+- eval_otal.cashprice: {'precision': 0.9558823529411765, 'recall': 0.9558823529411765, 'f1': 0.9558823529411765, 'number': 68}
+- eval_otal.changeprice: {'precision': 0.9655172413793104, 'recall': 1.0, 'f1': 0.9824561403508771, 'number': 56}
+- eval_otal.creditcardprice: {'precision': 0.7647058823529411, 'recall': 0.8125, 'f1': 0.787878787878788, 'number': 16}
+- eval_otal.emoneyprice: {'precision': 0.3333333333333333, 'recall': 0.5, 'f1': 0.4, 'number': 2}
+- eval_otal.menuqty_cnt: {'precision': 0.9333333333333333, 'recall': 0.9655172413793104, 'f1': 0.9491525423728815, 'number': 29}
+- eval_otal.menutype_cnt: {'precision': 1.0, 'recall': 0.7142857142857143, 'f1': 0.8333333333333333, 'number': 7}
+- eval_otal.total_etc: {'precision': 0.5, 'recall': 0.3333333333333333, 'f1': 0.4, 'number': 3}
+- eval_otal.total_price: {'precision': 0.9583333333333334, 'recall': 0.968421052631579, 'f1': 0.9633507853403142, 'number': 95}
+- eval_ub_total.discount_price: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 7}
+- eval_ub_total.etc: {'precision': 0.875, 'recall': 0.7777777777777778, 'f1': 0.823529411764706, 'number': 9}
+- eval_ub_total.service_price: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 12}
+- eval_ub_total.subtotal_price: {'precision': 0.9545454545454546, 'recall': 0.9692307692307692, 'f1': 0.9618320610687022, 'number': 65}
+- eval_ub_total.tax_price: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 43}
+- eval_overall_precision: 0.9522
+- eval_overall_recall: 0.9544
+- eval_overall_f1: 0.9533
+- eval_overall_accuracy: 0.9707
+- eval_runtime: 3.0438
+- eval_samples_per_second: 32.853
+- eval_steps_per_second: 4.271
+- epoch: 1.0
+- step: 50
+
+## 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: 1e-06
+- train_batch_size: 16
+- 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
+
+### Framework versions
+
+- Transformers 4.36.0
+- Pytorch 2.0.0
+- Datasets 2.16.1
+- Tokenizers 0.15.0

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a832169796266be04387239adcb0ff5709731bc7bcd7c91cbcfefacb16e8ab49
+oid sha256:b0c4ccfac9703de2700f9f8a8deef5682d64b84728ea3d9eca01808062d16e74
 size 450625884

preprocessor_config.json

@@ -0,0 +1,14 @@
+{
+  "apply_ocr": true,
+  "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

@@ -0,0 +1,37 @@
+{
+  "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

@@ -0,0 +1,79 @@
+{
+  "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
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [],
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "cls_token_box": [
+    0,
+    0,
+    0,
+    0
+  ],
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "never_split": null,
+  "only_label_first_subword": true,
+  "pad_token": "[PAD]",
+  "pad_token_box": [
+    0,
+    0,
+    0,
+    0
+  ],
+  "pad_token_label": -100,
+  "processor_class": "LayoutLMv2Processor",
+  "sep_token": "[SEP]",
+  "sep_token_box": [
+    1000,
+    1000,
+    1000,
+    1000
+  ],
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "LayoutLMv2Tokenizer",
+  "unk_token": "[UNK]"
+}