metadata

license: cc-by-sa-4.0
tags:
  - generated_from_trainer
datasets:
  - klue
metrics:
  - f1
base_model: klue/bert-base
model-index:
  - name: bert-base-finetuned-ynat
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: klue
          type: klue
          config: ynat
          split: validation
          args: ynat
        metrics:
          - type: f1
            value: 0.8696415258442162
            name: F1

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: 0.3642
F1: 0.8696

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: 512
eval_batch_size: 512
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	F1
No log	1.0	90	0.4440	0.8502
No log	2.0	180	0.3793	0.8667
No log	3.0	270	0.3642	0.8696
No log	4.0	360	0.3664	0.8693
No log	5.0	450	0.3675	0.8689

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu117
Datasets 2.13.1
Tokenizers 0.13.3