Kuongan / xlm-roberta-base-pcm-finetuned

huggingface.co
Total runs: 20
24-hour runs: 0
7-day runs: 0
30-day runs: 14
Model's Last Updated: January 29 2025
text-classification

Introduction of xlm-roberta-base-pcm-finetuned

Model Details of xlm-roberta-base-pcm-finetuned

xlm-roberta-base-pcm-finetuned

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: 0.4237
  • F1: 0.4302
  • Roc Auc: 0.6457
  • Accuracy: 0.3081
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: 32
  • seed: 42
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 20
Training results
Training Loss Epoch Step Validation Loss F1 Roc Auc Accuracy
0.4949 1.0 159 0.4592 0.1074 0.5319 0.1726
0.428 2.0 318 0.4154 0.2990 0.5972 0.2952
0.3804 3.0 477 0.4116 0.3552 0.6247 0.3016
0.3329 4.0 636 0.4237 0.4302 0.6457 0.3081
0.3116 5.0 795 0.4302 0.4257 0.6417 0.3097
0.2684 6.0 954 0.4445 0.4270 0.6463 0.3145
0.2433 7.0 1113 0.4619 0.4250 0.6455 0.3194
0.2221 8.0 1272 0.4965 0.4185 0.6495 0.3194
Framework versions
  • Transformers 4.47.0
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0

Runs of Kuongan xlm-roberta-base-pcm-finetuned on huggingface.co

20
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
14
30-day runs

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