metadata

base_model: csebuetnlp/banglabert
tags:
  - generated_from_trainer
metrics:
  - f1
  - accuracy
model-index:
  - name: banglabert-MLTC-BB1
    results: []

banglabert-MLTC-BB1

This model is a fine-tuned version of csebuetnlp/banglabert on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3577
F1: 0.8555
F1 Weighted: 0.8534
Roc Auc: 0.8534
Accuracy: 0.5733
Hamming Loss: 0.1465
Jaccard Score: 0.7475
Zero One Loss: 0.4267

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: 24
eval_batch_size: 24
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
0.5579	1.0	49	0.5012	0.7993	0.7864	0.7832	0.4267	0.2166	0.6657	0.5733
0.4039	2.0	98	0.4338	0.8318	0.8287	0.8218	0.5347	0.1780	0.7121	0.4653
0.3704	3.0	147	0.3728	0.8600	0.8604	0.8560	0.5861	0.1440	0.7544	0.4139
0.3117	4.0	196	0.3615	0.8568	0.8553	0.8528	0.5733	0.1472	0.7495	0.4267
0.2723	5.0	245	0.3514	0.8548	0.8537	0.8528	0.5784	0.1472	0.7464	0.4216
0.2709	6.0	294	0.3640	0.8469	0.8434	0.8438	0.5476	0.1562	0.7344	0.4524
0.224	7.0	343	0.3581	0.8488	0.8461	0.8477	0.5578	0.1523	0.7373	0.4422
0.2335	8.0	392	0.3622	0.8532	0.8510	0.8502	0.5656	0.1497	0.7440	0.4344
0.2453	9.0	441	0.3552	0.8573	0.8560	0.8554	0.5758	0.1446	0.7503	0.4242
0.2194	10.0	490	0.3577	0.8555	0.8534	0.8534	0.5733	0.1465	0.7475	0.4267

Framework versions

Transformers 4.41.1
Pytorch 2.1.2
Datasets 2.19.1
Tokenizers 0.19.1