willmyrick
/

layoutlm-funsd-tf

@@ -1,65 +1,65 @@
----
-license: mit
-base_model: microsoft/layoutlm-base-uncased
-tags:
-- generated_from_keras_callback
-model-index:
-- name: willmyrick/layoutlm-funsd-tf
-  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. -->
-# willmyrick/layoutlm-funsd-tf
-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: 0.2395
-- Validation Loss: 0.6723
-- Train Overall Precision: 0.7269
-- Train Overall Recall: 0.8013
-- Train Overall F1: 0.7623
-- Train Overall Accuracy: 0.8071
-- 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 |
-|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
-| 1.6854     | 1.3883          | 0.2671                  | 0.2494               | 0.2579           | 0.4942                 | 0     |
-| 1.1172     | 0.8636          | 0.5871                  | 0.6392               | 0.6121           | 0.7287                 | 1     |
-| 0.7701     | 0.7274          | 0.6558                  | 0.7170               | 0.6850           | 0.7690                 | 2     |
-| 0.5880     | 0.6978          | 0.6814                  | 0.7501               | 0.7141           | 0.7747                 | 3     |
-| 0.4569     | 0.7022          | 0.6984                  | 0.7612               | 0.7285           | 0.7710                 | 4     |
-| 0.3594     | 0.6280          | 0.7095                  | 0.7903               | 0.7477           | 0.8118                 | 5     |
-| 0.3095     | 0.6566          | 0.7298                  | 0.7832               | 0.7556           | 0.8085                 | 6     |
-| 0.2395     | 0.6723          | 0.7269                  | 0.8013               | 0.7623           | 0.8071                 | 7     |
-### Framework versions
-- Transformers 4.41.2
-- TensorFlow 2.16.1
-- Datasets 2.19.2
-- Tokenizers 0.19.1

+---
+license: mit
+base_model: microsoft/layoutlm-base-uncased
+tags:
+- generated_from_keras_callback
+model-index:
+- name: layoutlm-funsd-tf
+  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. -->
+# layoutlm-funsd-tf
+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: 0.2395
+- Validation Loss: 0.6723
+- Train Overall Precision: 0.7269
+- Train Overall Recall: 0.8013
+- Train Overall F1: 0.7623
+- Train Overall Accuracy: 0.8071
+- 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 |
+|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
+| 1.6854     | 1.3883          | 0.2671                  | 0.2494               | 0.2579           | 0.4942                 | 0     |
+| 1.1172     | 0.8636          | 0.5871                  | 0.6392               | 0.6121           | 0.7287                 | 1     |
+| 0.7701     | 0.7274          | 0.6558                  | 0.7170               | 0.6850           | 0.7690                 | 2     |
+| 0.5880     | 0.6978          | 0.6814                  | 0.7501               | 0.7141           | 0.7747                 | 3     |
+| 0.4569     | 0.7022          | 0.6984                  | 0.7612               | 0.7285           | 0.7710                 | 4     |
+| 0.3594     | 0.6280          | 0.7095                  | 0.7903               | 0.7477           | 0.8118                 | 5     |
+| 0.3095     | 0.6566          | 0.7298                  | 0.7832               | 0.7556           | 0.8085                 | 6     |
+| 0.2395     | 0.6723          | 0.7269                  | 0.8013               | 0.7623           | 0.8071                 | 7     |
+### Framework versions
+- Transformers 4.41.2
+- TensorFlow 2.16.1
+- Datasets 2.19.2
+- Tokenizers 0.19.1

config.json CHANGED Viewed

@@ -1,43 +1,43 @@
-{
-  "_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": "4.41.2",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 30522
-}

+{
+  "_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": "4.41.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}