pos_thai

This model is a fine-tuned version of Geotrend/bert-base-th-cased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0935
• Precision: 0.9525
• Recall: 0.9540
• F1: 0.9533
• Accuracy: 0.9693

Model description

This model is train on thai pos_tag datasets to help with pos tagging in Thai language.

Example

from transformers import AutoModelForTokenClassification, AutoTokenizer, TokenClassificationPipeline

model = AutoModelForTokenClassification.from_pretrained("lunarlist/pos_thai")
tokenizer = AutoTokenizer.from_pretrained("lunarlist/pos_thai")

pipeline = TokenClassificationPipeline(model=model, tokenizer=tokenizer, grouped_entities=True)
outputs = pipeline("ภาษาไทย ง่าย นิดเดียว")
print(outputs)

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1124	1.0	7344	0.1048	0.9505	0.9478	0.9492	0.9670
0.0866	2.0	14688	0.0935	0.9525	0.9540	0.9533	0.9693

Framework versions

• Transformers 4.34.1
• Pytorch 2.1.0+cu118
• Datasets 2.14.5
• Tokenizers 0.14.1