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my_awesome_wnut_model_2 – AI Model by priyanshug0405 | AlphaNeural AI
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priyanshug0405
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my_awesome_wnut_model_2
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transformers
tf
distilbert
token-classification
generated_from_keras_callback
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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priyanshug0405/my_awesome_wnut_model_2
This model is a fine-tuned version of
distilbert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.0378
Validation Loss: 0.0597
Train Precision: 0.9157
Train Recall: 0.9151
Train F1: 0.9154
Train Accuracy: 0.9807
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': 11250, '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
0.1337
0.0709
0.8861
0.8913
0.8887
0.9753
0
0.0562
0.0600
0.9113
0.9107
0.9110
0.9795
1
0.0378
0.0597
0.9157
0.9151
0.9154
0.9807
2
Framework versions
Transformers 4.37.0
TensorFlow 2.15.0
Datasets 2.16.1
Tokenizers 0.15.0
