Training in progress epoch 0

README.md

@@ -4,24 +4,24 @@ base_model: microsoft/layoutlm-base-uncased
 tags:
 - generated_from_keras_callback
 model-index:
-- name: layoutlm-funsd-tf
+- name: Matt6450/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
+# Matt6450/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: 0.2505
-- Validation Loss: 0.6780
-- Train Overall Precision: 0.7377
-- Train Overall Recall: 0.7973
-- Train Overall F1: 0.7663
-- Train Overall Accuracy: 0.8061
-- Epoch: 7
+- Train Loss: 1.8669
+- Validation Loss: 1.6316
+- Train Overall Precision: 0.0652
+- Train Overall Recall: 0.0502
+- Train Overall F1: 0.0567
+- Train Overall Accuracy: 0.3485
+- Epoch: 0
 
 ## Model description
 
@@ -40,21 +40,14 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- optimizer: {'inner_optimizer': {'module': 'transformers.optimization_tf', 'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': 2.9999999242136255e-05, 'decay': 0.0, 'beta_1': 0.8999999761581421, 'beta_2': 0.9990000128746033, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}, 'registered_name': 'AdamWeightDecay'}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
+- optimizer: {'inner_optimizer': {'module': 'transformers.optimization_tf', 'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': 1.9999999494757503e-05, 'decay': 0.0, 'beta_1': 0.8999999761581421, 'beta_2': 0.9990000128746033, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}, 'registered_name': 'AdamWeightDecay'}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
 - training_precision: mixed_float16
 
 ### Training results
 
 | Train Loss | Validation Loss | Train Overall Precision | Train Overall Recall | Train Overall F1 | Train Overall Accuracy | Epoch |
 |:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
-| 1.7445     | 1.4591          | 0.2596                  | 0.3161               | 0.2851           | 0.4800                 | 0     |
-| 1.1898     | 0.8586          | 0.5794                  | 0.6498               | 0.6126           | 0.7318                 | 1     |
-| 0.7791     | 0.7008          | 0.6577                  | 0.7637               | 0.7068           | 0.7795                 | 2     |
-| 0.5866     | 0.6335          | 0.7161                  | 0.7807               | 0.7470           | 0.8039                 | 3     |
-| 0.4528     | 0.6048          | 0.7234                  | 0.7978               | 0.7588           | 0.8174                 | 4     |
-| 0.3675     | 0.6302          | 0.7118                  | 0.7943               | 0.7508           | 0.8112                 | 5     |
-| 0.3039     | 0.6413          | 0.7297                  | 0.8018               | 0.7640           | 0.8110                 | 6     |
-| 0.2505     | 0.6780          | 0.7377                  | 0.7973               | 0.7663           | 0.8061                 | 7     |
+| 1.8669     | 1.6316          | 0.0652                  | 0.0502               | 0.0567           | 0.3485                 | 0     |
 
 
 ### Framework versions

logs/train/events.out.tfevents.1707203791.73191d6d4cc9.315.0.v2

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