sQuad_bertmodel1_ – AI Model by mallikrao2 | AlphaNeural AI

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sQuad_bertmodel1_

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mallikrao2/bert-base-uncased-finetuned

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

Train Loss: 0.5897
Train End Logits Accuracy: 0.8276
Train Start Logits Accuracy: 0.7901
Validation Loss: 1.0614
Validation End Logits Accuracy: 0.7313
Validation Start Logits Accuracy: 0.6992
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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 16596, '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
1.2874	0.6616	0.6200	1.0094	0.7239	0.6855	0
0.7993	0.7755	0.7332	0.9985	0.7323	0.7022	1
0.5897	0.8276	0.7901	1.0614	0.7313	0.6992	2

Framework versions

Transformers 4.29.2
TensorFlow 2.8.0
Datasets 2.12.0
Tokenizers 0.13.3