metadata

license: mit
base_model: xlm-roberta-base
tags:
  - generated_from_trainer
datasets:
  - xtreme
metrics:
  - f1
model-index:
  - name: multilingual-xlm-roberta-for-ner
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: xtreme
          type: xtreme
          config: PAN-X.de
          split: validation
          args: PAN-X.de
        metrics:
          - name: F1
            type: f1
            value: 0.8625248226950355

multilingual-xlm-roberta-for-ner

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

Loss: 0.1350
F1: 0.8625

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: 5e-05
train_batch_size: 24
eval_batch_size: 24
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	F1
0.2657	1.0	525	0.1631	0.8156
0.1275	2.0	1050	0.1370	0.8521
0.0797	3.0	1575	0.1350	0.8625

Framework versions

Transformers 4.38.1
Pytorch 2.1.2
Datasets 2.1.0
Tokenizers 0.15.2