This model is a fine-tuned version of mHossain/bengali_pos_v1_400000 on the pos_tag_100k dataset. It achieves the following results on the evaluation set:

Loss: 0.6185
Precision: 0.7517
Recall: 0.7533
F1: 0.7525
Accuracy: 0.8149

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.6508	1.0	67500	0.6325	0.7386	0.7396	0.7391	0.8041
0.5713	2.0	135000	0.6093	0.7487	0.7500	0.7493	0.8123
0.4789	3.0	202500	0.6185	0.7517	0.7533	0.7525	0.8149

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0

mHossain/bengali_pos_v1_500000

bengali_pos_v1_500000

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

mHossain/
bengali_pos_v1_500000