roberta-base-squad – AI Model by DLL888 | AlphaNeural AI

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DLL888/
roberta-base-squad

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DLL888/roberta-base-squad

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

Train Loss: 0.7054
Train End Logits Accuracy: 0.8022
Train Start Logits Accuracy: 0.7586
Validation Loss: 0.8224
Validation End Logits Accuracy: 0.7692
Validation Start Logits Accuracy: 0.7402
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': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 10570, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'passive_serialization': True}, 'warmup_steps': 500, 'power': 1.0, 'name': None}}, 'decay': 0.0, '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
1.1613	0.7038	0.6632	0.8676	0.7626	0.7342	0
0.7054	0.8022	0.7586	0.8224	0.7692	0.7402	1

Framework versions

Transformers 4.24.0
TensorFlow 2.9.2
Datasets 2.7.1
Tokenizers 0.13.2