PhoBert_category

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: 1.5453
• Accuracy: 0.7746
• F1: 0.7940

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: 128
• eval_batch_size: 128
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.4493	200	1.6763	0.7280	0.7130
2.1926	2.8986	400	1.4166	0.7623	0.7752
1.2092	4.3478	600	1.4280	0.7587	0.7775
1.2092	5.7971	800	1.3869	0.7794	0.7983
0.8036	7.2464	1000	1.5424	0.7685	0.7907
0.5470	8.6957	1200	1.5188	0.7783	0.7963
0.4097	10.0	1380	1.5453	0.7746	0.7940

Framework versions

• Transformers 5.10.1
• Pytorch 2.12.0+cu130
• Datasets 4.8.5
• Tokenizers 0.22.2