phibert-finetuned-ner-new-1 – AI Model by RUKESH | AlphaNeural AI

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RUKESH/
phibert-finetuned-ner-new-1

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token-classification

generated_from_trainer

dmis-lab/biobert-v1.1

autotrain_compatible

endpoints_compatible

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phibert-finetuned-ner-new-1

This model is a fine-tuned version of dmis-lab/biobert-v1.1 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0184
Precision: 0.9485
Recall: 0.9533
F1: 0.9509
Accuracy: 0.9963

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: 2e-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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.044	1.0	5915	0.0236	0.9014	0.9109	0.9061	0.9937
0.0266	2.0	11830	0.0209	0.9095	0.9271	0.9182	0.9943
0.0101	3.0	17745	0.0191	0.9335	0.9452	0.9393	0.9955
0.0104	4.0	23660	0.0181	0.9349	0.9483	0.9415	0.9959
0.0039	5.0	29575	0.0184	0.9485	0.9533	0.9509	0.9963

Framework versions

Transformers 4.32.1
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3