bert-finetuned-ner

This model is a fine-tuned version of ukr-models/xlm-roberta-base-uk on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.6570
• Precision: 0.0917
• Recall: 0.5882
• F1: 0.1587
• Accuracy: 0.1101

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: 1
• eval_batch_size: 1
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	3	1.7579	0.0917	0.5882	0.1587	0.1101
No log	2.0	6	1.6570	0.0917	0.5882	0.1587	0.1101

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.19.2
• Tokenizers 0.19.1