distilbert-base-uncased-mapa-ner-coarse_grained-v2

dmargutierrez/distilbert-base-uncased-mapa-ner-coarse_grained-v2

distilbert-base-uncased-mapa-ner-coarse_grained-v2 is a token classification model from dmargutierrez. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as apache-2.0.

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

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At a glance

Task: Token Classification
Library: transformers
License: apache-2.0
Model type: distilbert
Access: Public
Created: Mar 13, 2023
Updated: Mar 13, 2023
SHA: f7b55244

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Model card

From the Hugging Face model README

distilbert-base-uncased-mapa-ner-coarse_grained-v2

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1627
Precision: 0.7898
Recall: 0.4843
F1: 0.6004
Accuracy: 0.9857

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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0354	1.0	1739	0.0834	0.7023	0.4612	0.5568	0.9840
0.0255	2.0	3478	0.1034	0.8172	0.4355	0.5682	0.9852
0.0168	3.0	5217	0.0969	0.7714	0.4588	0.5754	0.9848
0.0132	4.0	6956	0.1042	0.7477	0.4838	0.5875	0.9852
0.0112	5.0	8695	0.1109	0.7421	0.4863	0.5876	0.9849
0.0085	6.0	10434	0.1076	0.7194	0.4951	0.5865	0.9850
0.0067	7.0	12173	0.1343	0.7828	0.4587	0.5784	0.9849
0.0047	8.0	13912	0.1252	0.7425	0.4840	0.5860	0.9853
0.0045	9.0	15651	0.1410	0.7943	0.4615	0.5838	0.9852
0.0035	10.0	17390	0.1311	0.7624	0.4929	0.5987	0.9857
0.003	11.0	19129	0.1494	0.8059	0.4691	0.5930	0.9855
0.0025	12.0	20868	0.1436	0.7674	0.4852	0.5945	0.9856
0.002	13.0	22607	0.1513	0.7778	0.4741	0.5891	0.9852
0.0014	14.0	24346	0.1577	0.7986	0.4726	0.5938	0.9855
0.0016	15.0	26085	0.1573	0.7802	0.4766	0.5917	0.9855
0.0011	16.0	27824	0.1599	0.7917	0.4723	0.5916	0.9856
0.0012	17.0	29563	0.1601	0.7848	0.4867	0.6008	0.9857
0.001	18.0	31302	0.1572	0.7614	0.4939	0.5991	0.9856
0.0011	19.0	33041	0.1602	0.7858	0.4870	0.6013	0.9857
0.0009	20.0	34780	0.1627	0.7898	0.4843	0.6004	0.9857

Framework versions

Transformers 4.26.0
Pytorch 1.13.1+cu117
Datasets 2.9.0
Tokenizers 0.13.2

Task: Token Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: Mar 13, 2023
Updated: Mar 13, 2023