README.md

metadata

license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
  - generated_from_trainer
datasets:
  - nsmc
metrics:
  - accuracy
model-index:
  - name: roberta
    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: 0.86608

roberta

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

• Loss: 0.3346
• Accuracy: 0.8661

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: 5e-06
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3619	1.0	9375	0.3406	0.8516
0.2989	2.0	18750	0.3243	0.8644
0.2655	3.0	28125	0.3346	0.8661

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.4
• Tokenizers 0.13.3