model

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: 0.2895
• Accuracy: 0.9434

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	1.1467	0.7871
No log	2.0	186	0.5867	0.9057
No log	3.0	279	0.3947	0.9272
No log	4.0	372	0.3269	0.9407
No log	5.0	465	0.3065	0.9407
0.7171	6.0	558	0.2895	0.9434
0.7171	7.0	651	0.2980	0.9407
0.7171	8.0	744	0.3061	0.9407
0.7171	9.0	837	0.3153	0.9407
0.7171	10.0	930	0.3177	0.9407

Framework versions

• Transformers 4.36.0
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0