xlm-roberta-base-language-detection-finetuned-ner-finetuned-ner

This model is a fine-tuned version of carexl8/xlm-roberta-base-language-detection-finetuned-ner on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0001
• Precision: 1.0000
• Recall: 1.0000
• F1: 1.0000
• Accuracy: 1.0000

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: 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
0.0007	1.0	1543	0.0001	1.0000	1.0000	1.0000	1.0000
0.0003	2.0	3086	0.0001	1.0000	1.0000	1.0000	1.0000

Framework versions

• Transformers 4.25.1
• Pytorch 1.13.0+cu116
• Datasets 2.8.0
• Tokenizers 0.13.2