jalaluddin94's picture
End of training
dafbd10
metadata
license: mit
base_model: xlm-roberta-large
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
model-index:
  - name: IndoJavaneseNLI-XLMR-large
    results: []

IndoJavaneseNLI-XLMR-large

This model is a fine-tuned version of xlm-roberta-large on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7328
  • Accuracy: 0.7770
  • Precision: 0.7770
  • Recall: 0.7770
  • F1 Score: 0.7772

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: 1e-06
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 101
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1 Score
1.4856 1.0 10330 1.7105 0.6063 0.6063 0.6063 0.6096
1.8291 2.0 20660 1.7699 0.6800 0.6800 0.6800 0.6785
1.7113 3.0 30990 1.6908 0.7260 0.7260 0.7260 0.7254
1.6058 4.0 41320 1.6276 0.7456 0.7456 0.7456 0.7451
1.3499 5.0 51650 1.6436 0.7565 0.7565 0.7565 0.7568
1.1362 6.0 61980 1.6715 0.7615 0.7615 0.7615 0.7619
1.1918 7.0 72310 1.7237 0.7738 0.7738 0.7738 0.7743
0.9035 8.0 82640 1.7436 0.7751 0.7751 0.7751 0.7750
0.9824 9.0 92970 1.7354 0.7806 0.7806 0.7806 0.7804
0.9303 10.0 103300 1.7328 0.7770 0.7770 0.7770 0.7772

Framework versions

  • Transformers 4.35.0.dev0
  • Pytorch 2.0.0
  • Datasets 2.1.0
  • Tokenizers 0.14.1