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End of training
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metadata
license: cc-by-sa-4.0
base_model: klue/bert-base
tags:
  - generated_from_trainer
datasets:
  - klue
metrics:
  - f1
model-index:
  - name: bert-base-finetuned-ynat
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: klue
          type: klue
          config: ynat
          split: validation
          args: ynat
        metrics:
          - name: F1
            type: f1
            value: 0.8673393457362918

bert-base-finetuned-ynat

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

  • Loss: 0.3817
  • F1: 0.8673

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: 256
  • eval_batch_size: 256
  • seed: 1
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss F1
No log 1.0 179 0.3817 0.8673
No log 2.0 358 0.4065 0.8634
0.2194 3.0 537 0.4077 0.8624
0.2194 4.0 716 0.4443 0.8584
0.2194 5.0 895 0.4795 0.8569
0.1477 6.0 1074 0.5159 0.8570
0.1477 7.0 1253 0.5445 0.8569
0.1477 8.0 1432 0.5711 0.8565
0.0849 9.0 1611 0.5913 0.8542
0.0849 10.0 1790 0.5945 0.8553

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1