CN_RoBERTa_Sci – AI Model by vishruthnath | AlphaNeural AI

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vishruthnath/
CN_RoBERTa_Sci

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text-classification

generated_from_trainer

FacebookAI/roberta-base

autotrain_compatible

endpoints_compatible

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CN_RoBERTa_Sci

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

Loss: 0.0236
F1: {'f1': 0.9961035068438405}
Accuracy: {'accuracy': 0.9961}

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:

learning_rate: 1e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy
0.3821	0.09	1000	0.3441	{'f1': 0.6707349429556912}	{'accuracy': 0.7518}
0.3263	0.18	2000	0.2076	{'f1': 0.8669489636728326}	{'accuracy': 0.8806}
0.1936	0.27	3000	0.0790	{'f1': 0.9856373429084382}	{'accuracy': 0.9856}
0.1056	0.36	4000	0.0421	{'f1': 0.9916925232709438}	{'accuracy': 0.9917}
0.0656	0.44	5000	0.0376	{'f1': 0.9938061938061938}	{'accuracy': 0.9938}
0.0486	0.53	6000	0.0267	{'f1': 0.9953032876986111}	{'accuracy': 0.9953}
0.0484	0.62	7000	0.0326	{'f1': 0.9952047952047953}	{'accuracy': 0.9952}
0.0356	0.71	8000	0.0230	{'f1': 0.9956995699569956}	{'accuracy': 0.9957}
0.0324	0.8	9000	0.0256	{'f1': 0.9958075464164502}	{'accuracy': 0.9958}
0.0381	0.89	10000	0.0261	{'f1': 0.9957038665201319}	{'accuracy': 0.9957}
0.0301	0.98	11000	0.0236	{'f1': 0.9961035068438405}	{'accuracy': 0.9961}

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0