sv1

bob-bob-bob-3/sv1

sv1 is a text classification model from bob-bob-bob-3. Use it when you need a label for a piece of text. 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: Text Classification
Library: transformers
License: mit
Model type: bert
Access: Public
Created: Jun 19, 2024
Updated: Jun 19, 2024
SHA: 1c537a2d

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Base models

indolem/indobert-base-uncased

Model card

From the Hugging Face model README

sv1

This model is a fine-tuned version of indolem/indobert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.3325
F1 macro: 0.3954
Weighted: 0.5529
Balanced accuracy: 0.5398

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: 7

Training results

Training Loss	Epoch	Step	Validation Loss	F1 macro	Weighted	Balanced accuracy
1.5316	1.0	154	1.5495	0.2252	0.3650	0.3588
1.2625	2.0	308	1.4130	0.3021	0.4392	0.4393
0.8381	3.0	462	1.4654	0.3616	0.5320	0.4578
0.6723	4.0	616	1.4752	0.4154	0.5946	0.5237
0.3447	5.0	770	1.6081	0.4057	0.6112	0.5217
0.2433	6.0	924	2.2897	0.4023	0.5488	0.5463
0.0404	7.0	1078	2.3325	0.3954	0.5529	0.5398

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1

Task: Text Classification
Library: transformers
Type: bert
License: mit
Created: Jun 19, 2024
Updated: Jun 19, 2024