ncert_bio – AI Model by S1d-dha-nth3 | AlphaNeural AI

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S1d-dha-nth3/
ncert_bio

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S1d-dha-nth3/ncert_bio

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: 2.6150
Validation Loss: 2.5873
Epoch: 14

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': 'AdamWeightDecay', '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': -647, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'passive_serialization': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
training_precision: float32

Training results

Train Loss	Validation Loss	Epoch
3.5434	2.8928	0
2.9142	2.6476	1
2.6884	2.5008	2
2.6079	2.5775	3
2.5748	2.5737	4
2.6031	2.5074	5
2.6237	2.5028	6
2.5849	2.5862	7
2.6154	2.4751	8
2.5584	2.4866	9
2.6107	2.5268	10
2.5852	2.5659	11
2.5915	2.5768	12
2.5678	2.7020	13
2.6150	2.5873	14

Framework versions

Transformers 4.22.1
TensorFlow 2.8.2
Datasets 2.4.0
Tokenizers 0.12.1