manasi – AI Model by vedantjumle | AlphaNeural AI

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vedantjumle/
manasi

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text-classification

generated_from_keras_callback

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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vedantjumle/manasi

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

Train Loss: 0.9757
Train Accuracy: 0.7839
Epoch: 18

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': 480, '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	Train Accuracy	Epoch
2.7486	0.4271	0
2.2633	0.4297	1
2.1244	0.4284	2
2.0740	0.4258	3
2.0444	0.4323	4
2.0005	0.4922	5
1.9095	0.5169	6
1.7609	0.5924	7
1.6275	0.6484	8
1.4806	0.6706	9
1.3658	0.7005	10
1.2600	0.7409	11
1.1962	0.7487	12
1.1222	0.7487	13
1.0866	0.7721	14
1.0440	0.7786	15
1.0203	0.7839	16
1.0053	0.7852	17
0.9757	0.7839	18

Framework versions

Transformers 4.34.0
TensorFlow 2.13.0
Datasets 2.14.5
Tokenizers 0.14.1