hmBERT-CoNLL-cp1

emilys/hmBERT-CoNLL-cp1

hmBERT-CoNLL-cp1 is a token classification model from emilys. 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: Oct 18, 2022
Updated: Oct 18, 2022
SHA: 059d85e6

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Datasets

conll2003

Model card

From the Hugging Face model README

hmBERT-CoNLL-cp1

This model is a fine-tuned version of dbmdz/bert-base-historic-multilingual-cased on the conll2003 dataset. It achieves the following results on the evaluation set:

Loss: 0.0710
Precision: 0.8690
Recall: 0.8888
F1: 0.8788
Accuracy: 0.9810

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

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	0.06	25	0.4115	0.3593	0.3708	0.3649	0.9002
No log	0.11	50	0.2263	0.6360	0.6898	0.6618	0.9456
No log	0.17	75	0.1660	0.7250	0.7582	0.7412	0.9564
No log	0.23	100	0.1520	0.7432	0.7775	0.7600	0.9597
No log	0.28	125	0.1343	0.7683	0.8103	0.7888	0.9645
No log	0.34	150	0.1252	0.7973	0.8230	0.8099	0.9691
No log	0.4	175	0.1021	0.8118	0.8398	0.8255	0.9724
No log	0.46	200	0.1056	0.8153	0.8411	0.8280	0.9727
No log	0.51	225	0.0872	0.8331	0.8612	0.8469	0.9755
No log	0.57	250	0.1055	0.8226	0.8418	0.8321	0.9725
No log	0.63	275	0.0921	0.8605	0.8640	0.8623	0.9767
No log	0.68	300	0.0824	0.8600	0.8787	0.8692	0.9788
No log	0.74	325	0.0834	0.8530	0.8771	0.8649	0.9787
No log	0.8	350	0.0758	0.8646	0.8876	0.8759	0.9800
No log	0.85	375	0.0727	0.8705	0.8866	0.8784	0.9810
No log	0.91	400	0.0734	0.8717	0.8899	0.8807	0.9811
No log	0.97	425	0.0713	0.8683	0.8889	0.8785	0.9810

Framework versions

Transformers 4.20.1
Pytorch 1.12.0
Datasets 2.4.0
Tokenizers 0.12.1

Task: Token Classification
Library: transformers
Type: bert
License: mit
Created: Oct 18, 2022
Updated: Oct 18, 2022