roberta-base-30percent-noise-finetuned-iso29148-req-detector – AI Model by kasrahabib | AlphaNeural AI

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kasrahabib/
roberta-base-30percent-noise-finetuned-iso29148-req-detector

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FacebookAI/roberta-base

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kasrahabib/roberta-base-30percent-noise-finetuned-iso29148-req-detector

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

Train Loss: 0.1130
Validation Loss: 1.3170
Epoch: 29

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': 3570, '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: float32

Training results

Train Loss	Validation Loss	Epoch
2.7366	2.1474	0
2.0578	1.2849	1
1.7330	0.9478	2
1.5185	0.8945	3
1.3298	0.8617	4
1.1132	0.8780	5
0.9545	0.9909	6
0.7872	0.9997	7
0.6438	1.1212	8
0.5418	1.1269	9
0.4570	1.1784	10
0.3900	1.1662	11
0.3229	1.3060	12
0.2866	1.2009	13
0.2535	1.3430	14
0.2206	1.3117	15
0.2148	1.3118	16
0.1990	1.3215	17
0.1884	1.3456	18
0.1761	1.3808	19
0.1632	1.3648	20
0.1509	1.2838	21
0.1447	1.3338	22
0.1460	1.3306	23
0.1386	1.3311	24
0.1315	1.3107	25
0.1214	1.3030	26
0.1225	1.3101	27
0.1181	1.3122	28
0.1130	1.3170	29

Framework versions

Transformers 4.42.3
TensorFlow 2.15.0
Datasets 2.19.1
Tokenizers 0.19.1