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siddharthtumre/
scibert-finetuned-ner

Name: scibert-finetuned-ner
Availability: InStock

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scibert-finetuned-ner

This model is a fine-tuned version of allenai/scibert_scivocab_uncased on the jnlpba dataset. It achieves the following results on the evaluation set:

Loss: 0.4717
Precision: 0.6737
Recall: 0.7757
F1: 0.7211
Accuracy: 0.9226

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: 16
eval_batch_size: 16
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
0.1608	1.0	2319	0.2431	0.6641	0.7581	0.7080	0.9250
0.103	2.0	4638	0.2916	0.6739	0.7803	0.7232	0.9228
0.0659	3.0	6957	0.3662	0.6796	0.7624	0.7186	0.9233
0.0393	4.0	9276	0.4222	0.6737	0.7771	0.7217	0.9225
0.025	5.0	11595	0.4717	0.6737	0.7757	0.7211	0.9226

Framework versions

Transformers 4.21.1
Pytorch 1.12.1+cu113
Datasets 2.4.0
Tokenizers 0.12.1

siddharthtumre/scibert-finetuned-ner

scibert-finetuned-ner

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

siddharthtumre/
scibert-finetuned-ner