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dipteshkanojia/
scibert_scivocab_uncased-finetuned-ner

Name: scibert_scivocab_uncased-finetuned-ner
Availability: InStock

generated_from_trainer

plo_dunfiltered_config

model-index

autotrain_compatible

endpoints_compatible

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scibert_scivocab_uncased-finetuned-ner

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

Loss: 0.1390
Precision: 0.9649
Recall: 0.9612
F1: 0.9631
Accuracy: 0.9594

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: 32
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 11

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1176	1.4	5000	0.1243	0.9570	0.9511	0.9540	0.9502
0.0973	2.81	10000	0.1129	0.9609	0.9572	0.9590	0.9553
0.0721	4.21	15000	0.1198	0.9645	0.9585	0.9615	0.9578
0.0634	5.62	20000	0.1259	0.9649	0.9589	0.9619	0.9582
0.0572	7.02	25000	0.1321	0.9653	0.9609	0.9631	0.9594
0.0472	8.43	30000	0.1390	0.9649	0.9612	0.9631	0.9594
0.0434	9.83	35000	0.1442	0.9656	0.9613	0.9634	0.9598

Framework versions

Transformers 4.18.0
Pytorch 1.10.1+cu111
Datasets 2.1.0
Tokenizers 0.12.1

dipteshkanojia/scibert_scivocab_uncased-finetuned-ner

scibert_scivocab_uncased-finetuned-ner

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

dipteshkanojia/
scibert_scivocab_uncased-finetuned-ner