metadata

license: gpl-3.0
tags:
  - generated_from_trainer
datasets:
  - mim_gold_ner
metrics:
  - precision
  - recall
  - f1
  - accuracy
widget:
  - text: >-
      Systurnar Guðrún og Monique átu einar á McDonalds og horfðu á Stöð 2, þar
      glitti í Bruce Willis leika í Die Hard 2.
base_model: vesteinn/IceBERT
model-index:
  - name: IceBERT-finetuned-ner
    results:
      - task:
          type: token-classification
          name: Token Classification
        dataset:
          name: mim_gold_ner
          type: mim_gold_ner
          args: mim-gold-ner
        metrics:
          - type: precision
            value: 0.9351994710160899
            name: Precision
          - type: recall
            value: 0.9440427188786294
            name: Recall
          - type: f1
            value: 0.9396002878813043
            name: F1
          - type: accuracy
            value: 0.9920330921021648
            name: Accuracy

IceBERT-finetuned-ner

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

Loss: 0.0347
Precision: 0.9352
Recall: 0.9440
F1: 0.9396
Accuracy: 0.9920

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
0.0568	1.0	2929	0.0386	0.9114	0.9162	0.9138	0.9897
0.0325	2.0	5858	0.0325	0.9300	0.9363	0.9331	0.9912
0.0184	3.0	8787	0.0347	0.9352	0.9440	0.9396	0.9920

Framework versions

Transformers 4.11.0
Pytorch 1.9.0+cu102
Datasets 1.12.1
Tokenizers 0.10.3