distilbert-base-uncased-finetuned-squad – AI Model by ademola277 | AlphaNeural AI

You can deploy this model and start earning money today!

ademola277/
distilbert-base-uncased-finetuned-squad

like

0

question-answering

generated_from_keras_callback

distilbert/distilbert-base-uncased

endpoints_compatible

Views

No views yet

ademola277/distilbert-base-uncased-finetuned-squad

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

Train Loss: 0.0000
Train End Logits Accuracy: 1.0
Train Start Logits Accuracy: 1.0
Validation Loss: 0.0010
Validation End Logits Accuracy: 0.9995
Validation Start Logits Accuracy: 1.0
Epoch: 2

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': 13587, '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: mixed_float16

Training results

Train Loss	Train End Logits Accuracy	Train Start Logits Accuracy	Validation Loss	Validation End Logits Accuracy	Validation Start Logits Accuracy	Epoch
0.0367	0.9968	0.9952	0.0026	0.9991	1.0	0
0.0003	1.0000	1.0000	0.0012	0.9995	1.0	1
0.0000	1.0	1.0	0.0010	0.9995	1.0	2

Framework versions

Transformers 4.31.0
TensorFlow 2.13.0
Datasets 2.12.0
Tokenizers 0.13.2