intent-classification

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: 0.1902
• Accuracy: 0.9597

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	93	1.0236	0.8468
No log	2.0	186	0.4412	0.9355
No log	3.0	279	0.2577	0.9462
No log	4.0	372	0.2303	0.9409
No log	5.0	465	0.2056	0.9516
0.623	6.0	558	0.2172	0.9516
0.623	7.0	651	0.1973	0.9516
0.623	8.0	744	0.1938	0.9597
0.623	9.0	837	0.1921	0.9543
0.623	10.0	930	0.1902	0.9597

Framework versions

• Transformers 4.39.3
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2