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t-vishnu/
my_awesome_model1

Name: my_awesome_model1
Availability: InStock

transformers

distilbert

text-classification

generated_from_keras_callback

distilbert/distilbert-base-uncased

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t-vishnu/my_awesome_model1

This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Train Loss: 0.3294
Validation Loss: 0.3083
Train Accuracy: {'accuracy': 0.8761904761904762}
Train Precision: {'precision': 0.9197572488199596}
Train Recall: {'recall': 0.7728045325779037}
Train F1 Score: {'f1': 0.8399014778325123}
Epoch: 0

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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2750, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
training_precision: float32

Training results

Train Loss	Validation Loss	Train Accuracy	Train Precision	Train Recall	Train F1 Score	Epoch
0.3294	0.3083	{'accuracy': 0.8761904761904762}	{'precision': 0.9197572488199596}	{'recall': 0.7728045325779037}	{'f1': 0.8399014778325123}	0

Framework versions

Transformers 4.40.2
TensorFlow 2.15.0
Datasets 2.19.1
Tokenizers 0.19.1