phunganhsang/hybrid_lexical_hosting_domain_full_cat_meta_phobert_default

hybrid_lexical_hosting_domain_full_cat_meta_freeze

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: 0.1485
• Accuracy: 0.9030
• F1: 0.8954

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: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 1725
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.2561	1.0	690	0.2016	0.8606	0.8505
0.1827	2.0	1380	0.1582	0.8963	0.8877
0.1485	3.0	2070	0.1485	0.9030	0.8954

Framework versions

• Transformers 4.57.1
• Pytorch 2.6.0+cu124
• Datasets 4.1.1
• Tokenizers 0.22.1