metadata

language:
  - en
  - is
  - multilingual
license: agpl-3.0
tags:
  - generated_from_trainer
datasets:
  - conll2003
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: XLMR-ENIS-finetuned-ner
    results:
      - task:
          type: token-classification
          name: Token Classification
        dataset:
          name: conll2003
          type: conll2003
          args: conll2003
        metrics:
          - type: precision
            value: 0.9398313331170938
            name: Precision
          - type: recall
            value: 0.9517943664285128
            name: Recall
          - type: f1
            value: 0.9457750214207026
            name: F1
          - type: accuracy
            value: 0.9853686150987764
            name: Accuracy

XLMR-ENIS-finetuned-ner

This model is a fine-tuned version of vesteinn/XLMR-ENIS on the conll2003 dataset. It achieves the following results on the evaluation set:

Loss: 0.0671
Precision: 0.9398
Recall: 0.9518
F1: 0.9458
Accuracy: 0.9854

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.2825	1.0	878	0.0712	0.9220	0.9379	0.9299	0.9815
0.0688	2.0	1756	0.0689	0.9354	0.9477	0.9415	0.9839
0.039	3.0	2634	0.0671	0.9398	0.9518	0.9458	0.9854

Framework versions

Transformers 4.10.3
Pytorch 1.9.0+cu102
Datasets 1.12.1
Tokenizers 0.10.3