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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - inspec
metrics:
  - f1
  - precision
  - recall
model-index:
  - name: bert-finetuned-inspec-3-epochs
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: inspec
          type: inspec
          args: extraction
        metrics:
          - name: F1
            type: f1
            value: 0.28328008519701814
          - name: Precision
            type: precision
            value: 0.26594090202177295
          - name: Recall
            type: recall
            value: 0.3030379746835443

bert-finetuned-inspec-3-epochs

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

  • Loss: 0.2728
  • F1: 0.2833
  • Precision: 0.2659
  • Recall: 0.3030

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: 8
  • eval_batch_size: 8
  • seed: 0
  • 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 Precision Recall
0.3338 1.0 125 0.2837 0.1401 0.1510 0.1306
0.2575 2.0 250 0.2658 0.2183 0.2519 0.1927
0.2259 3.0 375 0.2728 0.2833 0.2659 0.3030

Framework versions

  • Transformers 4.19.2
  • Pytorch 1.11.0+cu113
  • Datasets 2.2.1
  • Tokenizers 0.12.1