german_tc_professions_debates

johannabi/german_tc_professions_debates

german_tc_professions_debates is a token classification model from johannabi. 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: May 10, 2023
Updated: May 17, 2023
SHA: b0201621

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Model card

From the Hugging Face model README

german_tc_professions_debates

This model is a fine-tuned version of bert-base-german-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0487
Precision: 0.9439
Recall: 0.9739
F1: 0.9587
Accuracy: 0.9907

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
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	31	0.0423	0.9383	0.9646	0.9512	0.9894
No log	2.0	62	0.0513	0.9017	0.9757	0.9373	0.9883
No log	3.0	93	0.0444	0.9355	0.9739	0.9543	0.9902
No log	4.0	124	0.0474	0.9457	0.9739	0.9596	0.9909
No log	5.0	155	0.0487	0.9439	0.9739	0.9587	0.9907

Framework versions

Transformers 4.28.0
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3

Task: Token Classification
Library: transformers
Type: bert
License: mit
Created: May 10, 2023
Updated: May 17, 2023