Variome_5e-05_30_03

Brizape/Variome_5e-05_30_03

Variome_5e-05_30_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 30, 2023
Updated: Mar 30, 2023
SHA: ca02d3c3

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Model card

From the Hugging Face model README

Variome_5e-05_30_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: 0.0631
Precision: 0.5610
Recall: 0.5068
F1: 0.5325
Accuracy: 0.9859

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: 5e-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
0.6582	0.51	25	0.1765	0.0	0.0	0.0	0.9769
0.1545	1.02	50	0.1746	0.0	0.0	0.0	0.9769
0.1544	1.53	75	0.1770	0.0	0.0	0.0	0.9769
0.1608	2.04	100	0.1752	0.0	0.0	0.0	0.9769
0.1552	2.55	125	0.1726	0.0	0.0	0.0	0.9769
0.1591	3.06	150	0.1582	0.0	0.0	0.0	0.9769
0.1185	3.57	175	0.1142	0.2978	0.0703	0.1138	0.9778
0.0979	4.08	200	0.1046	0.2865	0.1584	0.2041	0.9792
0.0889	4.59	225	0.0923	0.3965	0.2151	0.2789	0.9811
0.0749	5.1	250	0.0819	0.4126	0.3295	0.3664	0.9827
0.0622	5.61	275	0.0756	0.4497	0.3987	0.4227	0.9838
0.0635	6.12	300	0.0699	0.4970	0.4355	0.4642	0.9850
0.048	6.63	325	0.0672	0.5225	0.4512	0.4842	0.9852
0.0486	7.14	350	0.0663	0.5457	0.4827	0.5122	0.9852
0.0464	7.65	375	0.0666	0.5623	0.4879	0.5225	0.9856
0.043	8.16	400	0.0636	0.5464	0.5005	0.5225	0.9857
0.0393	8.67	425	0.0636	0.5693	0.4869	0.5249	0.9860
0.036	9.18	450	0.0636	0.5641	0.4942	0.5268	0.9858
0.0373	9.69	475	0.0637	0.5735	0.5037	0.5363	0.9860
0.0382	10.2	500	0.0631	0.5610	0.5068	0.5325	0.9859

Framework versions

Transformers 4.27.4
Pytorch 1.13.1+cu116
Datasets 2.11.0
Tokenizers 0.13.2

Task: Token Classification
Library: transformers
Type: bert
License: mit
Created: Mar 30, 2023
Updated: Mar 30, 2023