End of training

README.md

@@ -0,0 +1,82 @@
+---
+library_name: transformers
+license: mit
+base_model: microsoft/layoutlm-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- funsd
+model-index:
+- name: layoutlm-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. -->
+
+# layoutlm-funsd
+
+This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on the funsd dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7672
+- Answer: {'precision': 0.7376681614349776, 'recall': 0.8133498145859085, 'f1': 0.7736625514403291, 'number': 809}
+- Header: {'precision': 0.37857142857142856, 'recall': 0.44537815126050423, 'f1': 0.4092664092664093, 'number': 119}
+- Question: {'precision': 0.8122109158186864, 'recall': 0.8244131455399061, 'f1': 0.8182665424044735, 'number': 1065}
+- Overall Precision: 0.7520
+- Overall Recall: 0.7973
+- Overall F1: 0.7740
+- Overall Accuracy: 0.8111
+
+## 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 | Answer                                                                                                     | Header                                                                                                      | Question                                                                                                   | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:----------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| 1.6896        | 1.0   | 19   | 1.4068          | {'precision': 0.0572737686139748, 'recall': 0.06180469715698393, 'f1': 0.05945303210463733, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}                                                 | {'precision': 0.4044834307992203, 'recall': 0.38967136150234744, 'f1': 0.3969392635102822, 'number': 1065} | 0.2449            | 0.2333         | 0.2390     | 0.4540           |
+| 1.1462        | 2.0   | 38   | 0.8626          | {'precision': 0.5445075757575758, 'recall': 0.7107540173053152, 'f1': 0.6166219839142091, 'number': 809}   | {'precision': 0.04878048780487805, 'recall': 0.01680672268907563, 'f1': 0.025, 'number': 119}               | {'precision': 0.6331615120274914, 'recall': 0.692018779342723, 'f1': 0.661283086585913, 'number': 1065}    | 0.5812            | 0.6593         | 0.6178     | 0.7285           |
+| 0.7687        | 3.0   | 57   | 0.7051          | {'precision': 0.6217264791464597, 'recall': 0.792336217552534, 'f1': 0.6967391304347825, 'number': 809}    | {'precision': 0.18421052631578946, 'recall': 0.11764705882352941, 'f1': 0.14358974358974358, 'number': 119} | {'precision': 0.6805084745762712, 'recall': 0.7539906103286385, 'f1': 0.7153674832962139, 'number': 1065}  | 0.6375            | 0.7316         | 0.6813     | 0.7678           |
+| 0.5961        | 4.0   | 76   | 0.6423          | {'precision': 0.6527918781725889, 'recall': 0.7948084054388134, 'f1': 0.7168338907469342, 'number': 809}   | {'precision': 0.26785714285714285, 'recall': 0.25210084033613445, 'f1': 0.2597402597402597, 'number': 119}  | {'precision': 0.7100949094046591, 'recall': 0.7727699530516432, 'f1': 0.7401079136690648, 'number': 1065}  | 0.6631            | 0.7506         | 0.7042     | 0.7923           |
+| 0.4739        | 5.0   | 95   | 0.6263          | {'precision': 0.7024972855591748, 'recall': 0.799752781211372, 'f1': 0.7479768786127167, 'number': 809}    | {'precision': 0.33070866141732286, 'recall': 0.35294117647058826, 'f1': 0.34146341463414637, 'number': 119} | {'precision': 0.7435897435897436, 'recall': 0.8169014084507042, 'f1': 0.778523489932886, 'number': 1065}   | 0.7029            | 0.7822         | 0.7404     | 0.8059           |
+| 0.3893        | 6.0   | 114  | 0.6456          | {'precision': 0.6912681912681913, 'recall': 0.8220024721878862, 'f1': 0.7509881422924901, 'number': 809}   | {'precision': 0.28169014084507044, 'recall': 0.33613445378151263, 'f1': 0.30651340996168586, 'number': 119} | {'precision': 0.768270944741533, 'recall': 0.8093896713615023, 'f1': 0.7882944673068131, 'number': 1065}   | 0.7040            | 0.7863         | 0.7428     | 0.8050           |
+| 0.3267        | 7.0   | 133  | 0.6813          | {'precision': 0.7297605473204105, 'recall': 0.7911001236093943, 'f1': 0.7591933570581256, 'number': 809}   | {'precision': 0.33070866141732286, 'recall': 0.35294117647058826, 'f1': 0.34146341463414637, 'number': 119} | {'precision': 0.7810283687943262, 'recall': 0.8272300469483568, 'f1': 0.8034655722754217, 'number': 1065}  | 0.7331            | 0.7842         | 0.7578     | 0.8019           |
+| 0.2731        | 8.0   | 152  | 0.6628          | {'precision': 0.7153846153846154, 'recall': 0.8046971569839307, 'f1': 0.7574171029668412, 'number': 809}   | {'precision': 0.3697478991596639, 'recall': 0.3697478991596639, 'f1': 0.3697478991596639, 'number': 119}    | {'precision': 0.7877145438121048, 'recall': 0.8187793427230047, 'f1': 0.8029465930018417, 'number': 1065}  | 0.7336            | 0.7863         | 0.7590     | 0.8137           |
+| 0.2425        | 9.0   | 171  | 0.6992          | {'precision': 0.7209302325581395, 'recall': 0.8046971569839307, 'f1': 0.7605140186915887, 'number': 809}   | {'precision': 0.3851851851851852, 'recall': 0.4369747899159664, 'f1': 0.4094488188976378, 'number': 119}    | {'precision': 0.801980198019802, 'recall': 0.8366197183098592, 'f1': 0.8189338235294118, 'number': 1065}   | 0.7417            | 0.7998         | 0.7697     | 0.8104           |
+| 0.2145        | 10.0  | 190  | 0.7271          | {'precision': 0.7373167981961668, 'recall': 0.8084054388133498, 'f1': 0.7712264150943396, 'number': 809}   | {'precision': 0.36075949367088606, 'recall': 0.4789915966386555, 'f1': 0.41155234657039713, 'number': 119}  | {'precision': 0.8250950570342205, 'recall': 0.8150234741784037, 'f1': 0.8200283419933868, 'number': 1065}  | 0.7530            | 0.7923         | 0.7721     | 0.8047           |
+| 0.1882        | 11.0  | 209  | 0.7348          | {'precision': 0.7400681044267877, 'recall': 0.8059332509270705, 'f1': 0.7715976331360946, 'number': 809}   | {'precision': 0.375, 'recall': 0.453781512605042, 'f1': 0.4106463878326997, 'number': 119}                  | {'precision': 0.8254716981132075, 'recall': 0.8215962441314554, 'f1': 0.8235294117647057, 'number': 1065}  | 0.7583            | 0.7933         | 0.7754     | 0.8103           |
+| 0.1668        | 12.0  | 228  | 0.7541          | {'precision': 0.7360178970917226, 'recall': 0.8133498145859085, 'f1': 0.7727539635936582, 'number': 809}   | {'precision': 0.3984375, 'recall': 0.42857142857142855, 'f1': 0.41295546558704455, 'number': 119}           | {'precision': 0.8007246376811594, 'recall': 0.8300469483568075, 'f1': 0.8151221761180267, 'number': 1065}  | 0.7493            | 0.7993         | 0.7735     | 0.8097           |
+| 0.1595        | 13.0  | 247  | 0.7616          | {'precision': 0.7370786516853932, 'recall': 0.8108776266996292, 'f1': 0.7722189523248971, 'number': 809}   | {'precision': 0.38345864661654133, 'recall': 0.42857142857142855, 'f1': 0.4047619047619047, 'number': 119}  | {'precision': 0.8153988868274582, 'recall': 0.8253521126760563, 'f1': 0.8203453103126458, 'number': 1065}  | 0.7549            | 0.7958         | 0.7748     | 0.8122           |
+| 0.1451        | 14.0  | 266  | 0.7638          | {'precision': 0.7361894024802705, 'recall': 0.8071693448702101, 'f1': 0.7700471698113207, 'number': 809}   | {'precision': 0.375886524822695, 'recall': 0.44537815126050423, 'f1': 0.40769230769230774, 'number': 119}   | {'precision': 0.8150557620817844, 'recall': 0.8234741784037559, 'f1': 0.8192433442316676, 'number': 1065}  | 0.7524            | 0.7943         | 0.7728     | 0.8110           |
+| 0.1449        | 15.0  | 285  | 0.7672          | {'precision': 0.7376681614349776, 'recall': 0.8133498145859085, 'f1': 0.7736625514403291, 'number': 809}   | {'precision': 0.37857142857142856, 'recall': 0.44537815126050423, 'f1': 0.4092664092664093, 'number': 119}  | {'precision': 0.8122109158186864, 'recall': 0.8244131455399061, 'f1': 0.8182665424044735, 'number': 1065}  | 0.7520            | 0.7973         | 0.7740     | 0.8111           |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

logs/events.out.tfevents.1725956688.layout-20240908-075832.34556.1

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3ef390952d126bc96632e7be3fa3e7c3a707acb4c1f0bb0a56976a803d59a555
-size 15088
+oid sha256:4c667de16be05639a041de522bbd9f535d0dac8a8160958d4632298b12fd1a6c
+size 16157

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6fd1a29144e77988c3f4df3c66257855906ca190656ae034d07195123d9bf13f
+oid sha256:7eddc7a4974e5a3e1ad82d6c717392f47876236d0a3e61ee69d10b599c345e96
 size 450558212

preprocessor_config.json

@@ -0,0 +1,13 @@
+{
+  "apply_ocr": true,
+  "do_resize": true,
+  "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 +1,80 @@
+{
+  "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": [],
+  "apply_ocr": false,
+  "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]"
+}