bert-base-multilingual-uncased-MLTC-rob

NaeemCSECUET18/bert-base-multilingual-uncased-MLTC-rob

bert-base-multilingual-uncased-MLTC-rob is a text classification model from NaeemCSECUET18. Use it when you need a label for a piece of text. 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: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Jun 3, 2024
Updated: Jun 3, 2024
SHA: 938d1867

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Base models

google-bert/bert-base-multilingual-uncased

Model card

From the Hugging Face model README

bert-base-multilingual-uncased-MLTC-rob

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

Loss: 0.3796
F1: 0.8594
F1 Weighted: 0.8595
Roc Auc: 0.8540
Accuracy: 0.5784
Hamming Loss: 0.1459
Jaccard Score: 0.7535
Zero One Loss: 0.4216

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: 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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	F1	F1 Weighted	Roc Auc	Accuracy	Hamming Loss	Jaccard Score	Zero One Loss
0.4034	1.0	146	0.3955	0.8282	0.8293	0.8291	0.5270	0.1710	0.7067	0.4730
0.4045	2.0	292	0.3662	0.8387	0.8397	0.8426	0.5578	0.1575	0.7222	0.4422
0.2843	3.0	438	0.3796	0.8594	0.8595	0.8540	0.5784	0.1459	0.7535	0.4216
0.209	4.0	584	0.3766	0.8446	0.8383	0.8425	0.5450	0.1575	0.7311	0.4550
0.2469	5.0	730	0.3608	0.8568	0.8548	0.8541	0.5784	0.1459	0.7494	0.4216
0.2266	6.0	876	0.3702	0.8462	0.8428	0.8451	0.5630	0.1549	0.7334	0.4370
0.1273	7.0	1022	0.3739	0.8561	0.8539	0.8547	0.5835	0.1452	0.7483	0.4165
0.1376	8.0	1168	0.3910	0.8568	0.8549	0.8567	0.5861	0.1433	0.7494	0.4139
0.1073	9.0	1314	0.3973	0.8566	0.8550	0.8567	0.5784	0.1433	0.7492	0.4216
0.0752	10.0	1460	0.4025	0.8542	0.8525	0.8541	0.5707	0.1459	0.7455	0.4293

Framework versions

Transformers 4.41.1
Pytorch 2.1.2
Datasets 2.19.1
Tokenizers 0.19.1

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Jun 3, 2024
Updated: Jun 3, 2024