chunwoolee0's picture
update model card README.md
59615c2
metadata
tags:
  - generated_from_trainer
datasets:
  - nsmc
metrics:
  - accuracy
  - f1
model-index:
  - name: nsmc_roberta_base_model
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: nsmc
          type: nsmc
          config: default
          split: test
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.91174
          - name: F1
            type: f1
            value: 0.9117155392338556

nsmc_roberta_base_model

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

  • Loss: 0.2570
  • Accuracy: 0.9117
  • F1: 0.9117

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: 64
  • eval_batch_size: 64
  • 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 Accuracy F1
0.2501 1.0 2344 0.2306 0.9072 0.9072
0.1805 2.0 4688 0.2306 0.9112 0.9112
0.1313 3.0 7032 0.2570 0.9117 0.9117

Framework versions

  • Transformers 4.30.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3