xlm-roberta-large-finetuned-wikiner-fr

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xlm-roberta-large-finetuned-wikiner-fr

This model is a fine-tuned version of xlm-roberta-large on the Alizee/wikiner_fr_mixed_caps.

Why this model?

Credits to Jean-Baptiste for building the current "best" model for French NER "camembert-ner" based on wikiNER (Jean-Baptiste/wikiner_fr).

xlm-roberta-large models fine-tuned on conll03 English and especially German were outperforming the Camembert-NER model in my own tasks. This inspired me to build a French version of the xlm-roberta-large models based on the wikiNER dataset, with the hope to create a slightly improved standard for French 4-entity NER.

Intended uses & limitations

4-entity NER for French, with the following tags:

Performance

It achieves the following results on the evaluation set:

• Loss: 0.0518
• Precision: 0.8881
• Recall: 0.9014
• F1: 0.8947
• Accuracy: 0.9855

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1.5e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.02
• num_epochs: 3

Training results

Framework versions

• Transformers 4.36.2
• Pytorch 2.0.1
• Datasets 2.16.1
• Tokenizers 0.15.0