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vladeachka/slot_token_classification_model

sourceHugging Facemitupdated 2y agoView on Hugging Face
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slottokenclassification_model

This model is a fine-tuned version of cointegrated/rubert-tiny2 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4739
  • Precision: 0.6455
  • Recall: 0.7092
  • F1: 0.6758
  • Accuracy: 0.8977

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 adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • lrschedulertype: linear
  • num_epochs: 5

Training results

Training LossEpochStepValidation LossPrecisionRecallF1Accuracy
0.4081.07200.49980.62260.66880.64490.8909
0.37582.014400.48150.63490.68680.65980.8953
0.33833.021600.47460.64050.70020.66900.8958
0.32784.028800.47330.65770.70320.67970.8977
0.30535.036000.47390.64550.70920.67580.8977

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0