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Librarian Bot: Add base_model information to model (#2)
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metadata
language: ga
license: apache-2.0
tags:
  - generated_from_trainer
  - irish
datasets:
  - wikiann
metrics:
  - precision
  - recall
  - f1
  - accuracy
widget:
  - text: Saolaíodh Pádraic Ó Conaire i nGaillimh sa bhliain 1882.
base_model: DCU-NLP/bert-base-irish-cased-v1
model-index:
  - name: bert-base-irish-cased-v1-finetuned-ner
    results:
      - task:
          type: token-classification
          name: Token Classification
        dataset:
          name: wikiann
          type: wikiann
          args: ga
        metrics:
          - type: precision
            value: 0.8190601668862538
            name: Precision
          - type: recall
            value: 0.8363228699551569
            name: Recall
          - type: f1
            value: 0.8276015087641446
            name: F1
          - type: accuracy
            value: 0.9306559069156423
            name: Accuracy

bert-base-irish-cased-v1-finetuned-ner

This model is a fine-tuned version of DCU-NLP/bert-base-irish-cased-v1 on the wikiann dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2468
  • Precision: 0.8191
  • Recall: 0.8363
  • F1: 0.8276
  • Accuracy: 0.9307

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: 5

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 63 0.4902 0.5579 0.5269 0.5420 0.8458
No log 2.0 126 0.3227 0.7169 0.7417 0.7291 0.8991
No log 3.0 189 0.2720 0.7895 0.7839 0.7867 0.9186
No log 4.0 252 0.2585 0.8128 0.8296 0.8211 0.9264
No log 5.0 315 0.2468 0.8191 0.8363 0.8276 0.9307

Framework versions

  • Transformers 4.12.5
  • Pytorch 1.10.0+cu111
  • Datasets 1.16.1
  • Tokenizers 0.10.3