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mariossmrs/greek-xlm-roberta-fire-type-multilabel-classification

sourceHugging Facemitupdated 5mo agoView on Hugging Face
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Model Card

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greek-xlm-roberta-fire-type-multilabel-classification

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: 0.1332
  • —Exact Match Ratio: 0.9091
  • —Macro Precision: 0.9440
  • —Macro Recall: 0.9340
  • —Macro F1: 0.9389

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
  • —trainbatchsize: 16
  • —evalbatchsize: 8
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 0.1
  • —num_epochs: 7
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossExact Match RatioMacro PrecisionMacro RecallMacro F1
0.63941.0550.59150.43180.30770.29790.3027
0.48402.01100.35460.76360.92600.72220.8007
0.26143.01650.18580.89090.93860.90460.9196
0.20294.02200.16950.89090.93970.90240.9206
0.15145.02750.15210.89550.95280.90210.9260
0.10566.03300.13080.92730.93840.96310.9506
0.08817.03850.13320.90910.94400.93400.9389

Framework versions

  • —Transformers 5.0.0
  • —Pytorch 2.10.0+cu128
  • —Datasets 4.0.0
  • —Tokenizers 0.22.2