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metadata
license: mit
base_model: xlm-roberta-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: xlm-roberta-base-Mixed-aug_delete
    results: []

xlm-roberta-base-Mixed-aug_delete

This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5308
  • Accuracy: 0.79
  • F1: 0.7759

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: 16
  • eval_batch_size: 16
  • 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 Accuracy F1
0.9389 1.0 87 0.6381 0.78 0.7289
0.6746 2.0 174 0.5763 0.79 0.7456
0.5322 3.0 261 0.6787 0.78 0.7539
0.4669 4.0 348 0.5214 0.79 0.7688
0.383 5.0 435 0.5308 0.79 0.7759

Framework versions

  • Transformers 4.32.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3