Variome_2e-05_29_03

Brizape/Variome_2e-05_29_03

Variome_2e-05_29_03 is a token classification model from Brizape. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Token Classification
Library: transformers
License: mit
Model type: bert
Access: Public
Created: Mar 29, 2023
Updated: Mar 29, 2023
SHA: b9c9af0b

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Model card

From the Hugging Face model README

Variome_2e-05_29_03

This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0928
Precision: 0.5437
Recall: 0.4211
F1: 0.4746
Accuracy: 0.9852

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
training_steps: 500

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
1.1552	5.0	25	0.1636	0.0	0.0	0.0	0.9794
0.1671	10.0	50	0.1345	0.0	0.0	0.0	0.9794
0.1297	15.0	75	0.1076	0.2683	0.0827	0.1264	0.9806
0.0995	20.0	100	0.1047	0.24	0.1353	0.1731	0.9810
0.0845	25.0	125	0.0987	0.2289	0.1429	0.1759	0.9813
0.0722	30.0	150	0.1001	0.2558	0.1654	0.2009	0.9816
0.0642	35.0	175	0.0994	0.3117	0.1805	0.2286	0.9821
0.0564	40.0	200	0.0938	0.3204	0.2481	0.2797	0.9817
0.0481	45.0	225	0.0935	0.4070	0.2632	0.3196	0.9833
0.0416	50.0	250	0.0913	0.4167	0.3383	0.3734	0.9836
0.0363	55.0	275	0.0911	0.4653	0.3534	0.4017	0.9847
0.0321	60.0	300	0.0909	0.4495	0.3684	0.4050	0.9842
0.0293	65.0	325	0.0918	0.5361	0.3910	0.4522	0.9852
0.0269	70.0	350	0.0936	0.5444	0.3684	0.4395	0.9853
0.0251	75.0	375	0.0936	0.5833	0.4211	0.4891	0.9858
0.0242	80.0	400	0.0920	0.5534	0.4286	0.4831	0.9854
0.0232	85.0	425	0.0928	0.5612	0.4135	0.4762	0.9855
0.0216	90.0	450	0.0928	0.5437	0.4211	0.4746	0.9852

Framework versions

Transformers 4.27.4
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2

Task: Token Classification
Library: transformers
Type: bert
License: mit
Created: Mar 29, 2023
Updated: Mar 29, 2023