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benitezfj/langid-ner-xlm-v-base

sourceHugging Facemitupdated 10mo agoView on Hugging Face
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langid-ner-xlm-v-base

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

  • —Loss: 0.4352
  • —Precision: 0.7966
  • —Recall: 0.7905
  • —F1: 0.7935
  • —Accuracy: 0.8978

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: 16
  • —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
  • —num_epochs: 10

Training results

Training LossEpochStepValidation LossPrecisionRecallF1Accuracy
No log1.0721.54460.56710.56710.56710.5366
No log2.01441.00010.61460.63670.62550.7876
No log3.02160.78110.64880.64930.64910.8160
No log4.02880.65400.71650.73150.72400.8648
No log5.03600.58710.73230.73660.73440.8725
No log6.04320.55910.73630.74240.73930.8719
0.9667.05040.52820.74540.74660.74600.8812
0.9668.05760.50950.74380.75250.74810.8792
0.9669.06480.49400.74440.75250.74840.8792
0.96610.07200.49230.74320.75250.74780.8802

Framework versions

  • —Transformers 4.57.2
  • —Pytorch 2.9.0+cu126
  • —Datasets 4.0.0
  • —Tokenizers 0.22.1