scibert-finetuned-ner – AI Model by eeshclusive | AlphaNeural AI

You can deploy this model and start earning money today!

eeshclusive/
scibert-finetuned-ner

like

0

token-classification

generated_from_trainer

allenai/scibert_scivocab_cased

autotrain_compatible

endpoints_compatible

Views

No views yet

scibert-finetuned-ner

This model is a fine-tuned version of allenai/scibert_scivocab_cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3459
Precision: 0.5666
Recall: 0.5191
F1: 0.5418
Accuracy: 0.9363

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	121	0.3648	0.3157	0.3390	0.3269	0.8945
No log	2.0	242	0.3177	0.5280	0.3348	0.4097	0.9253
No log	3.0	363	0.2599	0.5143	0.4326	0.4700	0.9315
No log	4.0	484	0.2825	0.5360	0.4227	0.4726	0.9336
0.2574	5.0	605	0.2968	0.5473	0.4922	0.5183	0.9350
0.2574	6.0	726	0.3193	0.5857	0.4894	0.5332	0.9377
0.2574	7.0	847	0.3327	0.5513	0.4879	0.5177	0.9356
0.2574	8.0	968	0.3315	0.5658	0.5121	0.5376	0.9363
0.0678	9.0	1089	0.3413	0.5465	0.5163	0.5310	0.9361
0.0678	10.0	1210	0.3459	0.5666	0.5191	0.5418	0.9363

Framework versions

Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1