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: 0.871180664370084

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: 0.3609
F1: 0.8712

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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	F1
No log	1.0	179	0.3979	0.8611
No log	2.0	358	0.3773	0.8669
0.3007	3.0	537	0.3609	0.8712
0.3007	4.0	716	0.3708	0.8708
0.3007	5.0	895	0.3720	0.8697

Framework versions

Transformers 4.21.0
Pytorch 1.12.0+cu113
Datasets 2.4.0
Tokenizers 0.12.1