You can deploy this model and start earning money today!

machiwao/
my_awesome_model

Name: my_awesome_model
Availability: InStock

transformers

distilbert

question-answering

generated_from_keras_callback

distilbert/distilbert-base-uncased

finetune

apache-2.0

endpoints_compatible

Views

No views yet

machiwao/my_awesome_model

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: 1.4826
Validation Loss: 2.0951
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': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 624, '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	Epoch
1.4843	2.0951	0
1.4826	2.0951	1

Framework versions

Transformers 4.52.4
TensorFlow 2.18.0
Datasets 3.6.0
Tokenizers 0.21.1