distilbert-base-uncased-finetuned-squad – AI Model by priyankav | AlphaNeural AI

You can deploy this model and start earning money today!

priyankav/
distilbert-base-uncased-finetuned-squad

like

0

question-answering

generated_from_keras_callback

endpoints_compatible

Views

No views yet

priyankavalappil/distilbert-base-uncased-finetuned-squad

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: 0.9684
Train End Logits Accuracy: 0.7305
Train Start Logits Accuracy: 0.6893
Validation Loss: 1.1278
Validation End Logits Accuracy: 0.6999
Validation Start Logits Accuracy: 0.6635
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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 11064, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
training_precision: float32

Training results

Train Loss	Train End Logits Accuracy	Train Start Logits Accuracy	Validation Loss	Validation End Logits Accuracy	Validation Start Logits Accuracy	Epoch
1.5059	0.6070	0.5685	1.1518	0.6816	0.6482	0
0.9684	0.7305	0.6893	1.1278	0.6999	0.6635	1

Framework versions

Transformers 4.22.2
TensorFlow 2.8.2
Datasets 2.5.2
Tokenizers 0.12.1