intent-classification-v2.1

This model is a fine-tuned version of vinai/phobert-base-v2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1893
• Accuracy: 0.9626

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: 5e-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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	101	1.0475	0.8653
No log	2.0	202	0.4967	0.9252
No log	3.0	303	0.2887	0.9401
No log	4.0	404	0.1985	0.9651
0.6678	5.0	505	0.2150	0.9551
0.6678	6.0	606	0.2009	0.9576
0.6678	7.0	707	0.2047	0.9601
0.6678	8.0	808	0.1931	0.9626
0.6678	9.0	909	0.1908	0.9651
0.0698	10.0	1010	0.1893	0.9626

Framework versions

• Transformers 4.40.1
• Pytorch 2.2.1+cu121
• Datasets 2.19.0
• Tokenizers 0.19.1