xlm-roberta-large-finetuned-ner

This model is a fine-tuned version of xlm-roberta-large on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.0541
• Precision: 0.1505
• Recall: 0.0201
• F1: 0.0355
• Accuracy: 0.7304

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: 0.0002
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
1.0694	0.37	7000	1.0495	0.1505	0.0201	0.0355	0.7304
1.0581	0.74	14000	1.0539	0.1505	0.0201	0.0355	0.7304

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.2+cu121
• Datasets 2.16.1
• Tokenizers 0.15.0