FULL-3epoch-XLMRoBERTa-finetuned-CEFR_ner-60000news

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

• Loss: 0.2571
• Accuracy: 0.3011
• Precision: 0.7306
• Recall: 0.6846
• F1: 0.5945

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
• gradient_accumulation_steps: 8
• total_train_batch_size: 512
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	0.9923	97	0.5290	0.2637	0.6408	0.5061	0.4053
No log	1.9949	195	0.2969	0.2962	0.7163	0.6474	0.5560
No log	2.9770	291	0.2571	0.3011	0.7306	0.6846	0.5945

Framework versions

• Transformers 4.41.2
• Pytorch 2.2.1
• Datasets 2.19.2
• Tokenizers 0.19.1