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metadata
language:
  - en
license: mit
base_model: xlm-roberta-base
tags:
  - generated_from_trainer
datasets:
  - tmnam20/VieGLUE
metrics:
  - accuracy
model-index:
  - name: xlm-roberta-base-vsfc-1
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: tmnam20/VieGLUE/VSFC
          type: tmnam20/VieGLUE
          config: vsfc
          split: validation
          args: vsfc
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9450410612760581

xlm-roberta-base-vsfc-1

This model is a fine-tuned version of xlm-roberta-base on the tmnam20/VieGLUE/VSFC dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2253
  • Accuracy: 0.9450

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: 32
  • eval_batch_size: 16
  • seed: 1
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.207 1.4 500 0.2353 0.9400
0.1438 2.79 1000 0.2245 0.9450

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.2.0.dev20231203+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0