This model is a fine-tuned version of pythainlp/thainer-corpus-v2-base-model on the lst20 dataset. It achieves the following results on the evaluation set:

Loss: 0.1293
Precision: 0.7684
Recall: 0.8120
F1: 0.7896
Accuracy: 0.9565

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: 32
eval_batch_size: 32
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
0.1226	1.0	1978	0.1416	0.7414	0.7802	0.7603	0.9518
0.098	2.0	3956	0.1324	0.7602	0.7966	0.7780	0.9545
0.0895	3.0	5934	0.1293	0.7684	0.8120	0.7896	0.9565

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0

thanaphatt1/WangchanBERTa-LST20

toneza

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

thanaphatt1/
WangchanBERTa-LST20