gua-spa-2023-langid-ner-multilingual-bert-gn-base-cased

This model is a fine-tuned version of mmaguero/multilingual-bert-gn-base-cased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.5469
• Precision: 0.1284
• Recall: 0.0627
• F1: 0.0843
• Accuracy: 0.5285

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: 16
• eval_batch_size: 16
• 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: 0.5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	0.5	36	1.5850	0.1194	0.0548	0.0751	0.5186

Framework versions

• Transformers 4.57.1
• Pytorch 2.8.0+cu126
• Datasets 4.0.0
• Tokenizers 0.22.1