End of training

README.md

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+---
+tags:
+- generated_from_keras_callback
+model-index:
+- name: layout_lm_fine_tune_funsd_dataset
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information Keras had access to. You should
+probably proofread and complete it, then remove this comment. -->
+
+# layout_lm_fine_tune_funsd_dataset
+
+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:
+- Train Loss: 0.2499
+- Validation Loss: 0.6927
+- Train Overall Precision: 0.7401
+- Train Overall Recall: 0.8159
+- Train Overall F1: 0.7761
+- Train Overall Accuracy: 0.8046
+- Epoch: 7
+
+## 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:
+- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 3e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
+- training_precision: mixed_float16
+
+### Training results
+
+| Train Loss | Validation Loss | Train Overall Precision | Train Overall Recall | Train Overall F1 | Train Overall Accuracy | Epoch |
+|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
+| 1.7326     | 1.4249          | 0.2261                  | 0.2052               | 0.2151           | 0.5250                 | 0     |
+| 1.1901     | 0.9108          | 0.5753                  | 0.6207               | 0.5972           | 0.7156                 | 1     |
+| 0.7777     | 0.7170          | 0.6511                  | 0.7396               | 0.6925           | 0.7679                 | 2     |
+| 0.5681     | 0.6626          | 0.6988                  | 0.7777               | 0.7362           | 0.7920                 | 3     |
+| 0.4449     | 0.6512          | 0.7236                  | 0.7762               | 0.7490           | 0.8013                 | 4     |
+| 0.3576     | 0.6547          | 0.7251                  | 0.7888               | 0.7556           | 0.8073                 | 5     |
+| 0.2910     | 0.6700          | 0.7380                  | 0.7958               | 0.7658           | 0.8106                 | 6     |
+| 0.2499     | 0.6927          | 0.7401                  | 0.8159               | 0.7761           | 0.8046                 | 7     |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- TensorFlow 2.12.0
+- Datasets 2.11.0
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "microsoft/layoutlm-base-uncased",
+  "architectures": [
+    "LayoutLMForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "O",
+    "1": "B-HEADER",
+    "2": "I-HEADER",
+    "3": "B-QUESTION",
+    "4": "I-QUESTION",
+    "5": "B-ANSWER",
+    "6": "I-ANSWER"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "B-ANSWER": 5,
+    "B-HEADER": 1,
+    "B-QUESTION": 3,
+    "I-ANSWER": 6,
+    "I-HEADER": 2,
+    "I-QUESTION": 4,
+    "O": 0
+  },
+  "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",
+  "transformers_version": "4.28.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

tf_model.h5

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+oid sha256:3ecb6f3338adc6d56442e0af447e0d8b7532c4e73d7a1a32feb8b50896cfeb6c
+size 450829256