Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
bert-base-cased-mcq-swag – AI Model by sahithya20 | AlphaNeural AI
You can deploy this model and start earning money today!
sahithya20
/
bert-base-cased-mcq-swag
like
0
transformers
tf
tensorboard
bert
multiple-choice
generated_from_keras_callback
google-bert/bert-base-cased
finetune
apache-2.0
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
sahithya20/bert-base-cased-mcq-swag
This model is a fine-tuned version of
bert-base-cased
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.4182
Train Accuracy: 0.8560
Validation Loss: 0.9197
Validation Accuracy: 0.6680
Epoch: 1
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': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 250, '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
Validation Loss
Validation Accuracy
Epoch
1.0536
0.5440
0.8819
0.6500
0
0.4182
0.8560
0.9197
0.6680
1
Framework versions
Transformers 4.38.2
TensorFlow 2.15.0
Datasets 2.18.0
Tokenizers 0.15.2
