w11wo's picture
End of training
cc9cff5
metadata
license: mit
base_model: xlm-roberta-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: xlm-roberta-base-reddit-indonesia-sarcastic
    results: []

xlm-roberta-base-reddit-indonesia-sarcastic

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

  • Loss: 0.5093
  • Accuracy: 0.8031
  • F1: 0.5690
  • Precision: 0.6284
  • Recall: 0.5198

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
0.5174 1.0 309 0.4618 0.7725 0.4641 0.5650 0.3938
0.4462 2.0 618 0.4407 0.7994 0.5428 0.6316 0.4759
0.3952 3.0 927 0.4690 0.8037 0.4991 0.69 0.3909
0.3525 4.0 1236 0.4905 0.8079 0.5152 0.6990 0.4079
0.3102 5.0 1545 0.4741 0.8122 0.5917 0.6486 0.5439
0.2645 6.0 1854 0.4964 0.8101 0.5976 0.6358 0.5637
0.2168 7.0 2163 0.5216 0.8079 0.5824 0.6385 0.5354
0.1759 8.0 2472 0.6826 0.8044 0.5818 0.6254 0.5439

Framework versions

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