README.md

metadata

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: train
          args: ynat
        metrics:
          - name: F1
            type: f1
            value: 0.7926757740066559

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: 0.7504
• F1: 0.7927

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: 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	F1
No log	1.0	18	1.3143	0.6445
No log	2.0	36	0.8546	0.7758
No log	3.0	54	0.7504	0.7927

Framework versions

• Transformers 4.21.0
• Pytorch 1.12.0+cu113
• Datasets 2.4.0
• Tokenizers 0.12.1