metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - article50v2_wikigold_split
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: Article_50v2_NER_Model_3Epochs_UNAUGMENTED
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: article50v2_wikigold_split
          type: article50v2_wikigold_split
          args: default
        metrics:
          - name: Precision
            type: precision
            value: 0
          - name: Recall
            type: recall
            value: 0
          - name: F1
            type: f1
            value: 0
          - name: Accuracy
            type: accuracy
            value: 0.7776133458899502

Article_50v2_NER_Model_3Epochs_UNAUGMENTED

This model is a fine-tuned version of bert-base-cased on the article50v2_wikigold_split dataset. It achieves the following results on the evaluation set:

Loss: 0.7694
Precision: 0.0
Recall: 0.0
F1: 0.0
Accuracy: 0.7776

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: 8
eval_batch_size: 8
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
No log	1.0	6	0.9910	0.1161	0.0044	0.0085	0.7766
No log	2.0	12	0.8031	0.0	0.0	0.0	0.7776
No log	3.0	18	0.7694	0.0	0.0	0.0	0.7776

Framework versions

Transformers 4.17.0
Pytorch 1.11.0+cu113
Datasets 2.4.0
Tokenizers 0.11.6