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my-awesome-address-tokenizer-model-v2 – AI Model by bhattronak | AlphaNeural AI
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bhattronak
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my-awesome-address-tokenizer-model-v2
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transformers
tf
safetensors
distilbert
token-classification
generated_from_keras_callback
autotrain_compatible
endpoints_compatible
us
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bhattronak/my-awesome-address-tokenizer-model-v2
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.4448
Validation Loss: 0.4385
Train Precision: 0.8173
Train Recall: 0.8495
Train F1: 0.8331
Train Accuracy: 0.8510
Epoch: 2
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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 489, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
training_precision: float32
Training results
Train Loss
Validation Loss
Train Precision
Train Recall
Train F1
Train Accuracy
Epoch
1.1961
0.6422
0.7391
0.7729
0.7556
0.7799
0
0.5690
0.4755
0.7781
0.8436
0.8095
0.8383
1
0.4448
0.4385
0.8173
0.8495
0.8331
0.8510
2
Framework versions
Transformers 4.35.0
TensorFlow 2.14.0
Datasets 2.14.6
Tokenizers 0.14.1
