distilbert-base-uncased-finetuned-squad-batchsize-8 – AI Model by TreyJ | AlphaNeural AI

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TreyJ/
distilbert-base-uncased-finetuned-squad-batchsize-8

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TreyJ/distilbert-base-uncased-finetuned-squad-batchsize-8

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: 1.0566
Train End Logits Accuracy: 0.7096
Train Start Logits Accuracy: 0.6701
Validation Loss: 1.1422
Validation End Logits Accuracy: 0.6940
Validation Start Logits Accuracy: 0.6575
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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 22130, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, '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
1.5985	0.5877	0.5521	1.1950	0.6779	0.6395	0
1.0566	0.7096	0.6701	1.1422	0.6940	0.6575	1

Framework versions

Transformers 4.28.0.dev0
TensorFlow 2.12.0
Datasets 2.11.0
Tokenizers 0.13.3