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xlm-roberta-base-finetuned-pos-tr

This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2340
  • Precision: 0.9437
  • Recall: 0.9445
  • F1: 0.9441
  • Accuracy: 0.9654

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.3157 1.0 836 0.1525 0.9241 0.9352 0.9296 0.9552
0.1291 2.0 1672 0.1430 0.9286 0.9337 0.9311 0.9573
0.1021 3.0 2508 0.1231 0.9344 0.9405 0.9374 0.9617
0.0868 4.0 3344 0.1220 0.9393 0.9422 0.9407 0.9635
0.0723 5.0 4180 0.1224 0.9419 0.9457 0.9438 0.9657
0.0634 6.0 5016 0.1329 0.9413 0.9431 0.9422 0.9641
0.0545 7.0 5852 0.1441 0.9422 0.9440 0.9431 0.9646
0.0476 8.0 6688 0.1541 0.9422 0.9431 0.9427 0.9643
0.0419 9.0 7524 0.1603 0.9428 0.9455 0.9442 0.9652
0.0357 10.0 8360 0.1693 0.9439 0.9455 0.9447 0.9649
0.0313 11.0 9196 0.1770 0.9441 0.9451 0.9446 0.9653
0.0274 12.0 10032 0.1880 0.9414 0.9435 0.9425 0.9645
0.0235 13.0 10868 0.1986 0.9452 0.9441 0.9446 0.9653
0.021 14.0 11704 0.2081 0.9436 0.9439 0.9438 0.9650
0.0177 15.0 12540 0.2116 0.9433 0.9440 0.9437 0.9651
0.0153 16.0 13376 0.2174 0.9457 0.9452 0.9454 0.9662
0.0132 17.0 14212 0.2252 0.9431 0.9441 0.9436 0.9649
0.0126 18.0 15048 0.2292 0.9432 0.9441 0.9437 0.9653
0.0106 19.0 15884 0.2338 0.9440 0.9442 0.9441 0.9654
0.0106 20.0 16720 0.2340 0.9437 0.9445 0.9441 0.9654

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.2.1+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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