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w11wo/xlm-roberta-large-twitter-indonesia-sarcastic

🤗 Hugging Face sourcetext-classificationmit560M params2.2 GBsafetensors✓ 4 checksumsupdated today
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xlm-roberta-large-twitter-indonesia-sarcastic

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: 0.4322
  • Accuracy: 0.8885
  • F1: 0.7692
  • Precision: 0.7937
  • Recall: 0.7463

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-05
  • train_batch_size: 32
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 100.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
0.5862 1.0 59 0.5304 0.75 0.0 0.0 0.0
0.5168 2.0 118 0.4897 0.75 0.0 0.0 0.0
0.4771 3.0 177 0.4535 0.7948 0.3373 0.875 0.2090
0.4101 4.0 236 0.4235 0.7910 0.6585 0.5567 0.8060
0.3225 5.0 295 0.4733 0.8507 0.5918 0.9355 0.4328
0.2246 6.0 354 0.3362 0.8694 0.7009 0.82 0.6119
0.166 7.0 413 0.3672 0.8769 0.7227 0.8269 0.6418
0.0989 8.0 472 0.3835 0.8769 0.7626 0.7361 0.7910
0.0797 9.0 531 0.4379 0.8993 0.7939 0.8125 0.7761
0.08 10.0 590 0.7677 0.8545 0.7451 0.6628 0.8507
0.0505 11.0 649 0.7316 0.8806 0.7288 0.8431 0.6418
0.073 12.0 708 0.4796 0.9104 0.8182 0.8308 0.8060
0.05 13.0 767 0.8469 0.8694 0.7059 0.8077 0.6269
0.0583 14.0 826 0.7266 0.8918 0.7563 0.8654 0.6716
0.0275 15.0 885 0.8974 0.8918 0.7387 0.9318 0.6119

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.1.1+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0