punctuation-tedtalk2012-bert-base-full-text-bert

tiagoblima/punctuation-tedtalk2012-bert-base-full-text-bert

punctuation-tedtalk2012-bert-base-full-text-bert is a token classification model from tiagoblima. 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. --

Downloads · 30 days

1% of all-time downloads

All-time downloads

336

Public

Repo size

867 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin433 MB · 100%

At a glance

Task: Token Classification
Library: transformers
License: mit
Model type: bert
Access: Public
Created: Mar 4, 2023
Updated: Mar 4, 2023
SHA: 76715df6

Try a prompt

Datasets

tiagoblima/punctuation-tedtalk2012-full-text-bert

Model card

From the Hugging Face model README

punctuation-tedtalk2012-bert-base-full-text-bert

This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on the tiagoblima/punctuation-tedtalk2012-full-text-bert dataset. It achieves the following results on the evaluation set:

Loss: 0.1495
Precision: 0.7179
Recall: 0.7416
F1: 0.7295
Accuracy: 0.9417

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	197	0.1495	0.7179	0.7416	0.7295	0.9417

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2

Task: Token Classification
Library: transformers
Type: bert
License: mit
Created: Mar 4, 2023
Updated: Mar 4, 2023