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Pablo94/roberta-base-bne-finetuned-detests-wandb24

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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roberta-base-bne-finetuned-detests-wandb24

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

  • —Loss: 0.3730
  • —Accuracy: 0.8592
  • —F1-score: 0.7922
  • —Precision: 0.8046
  • —Recall: 0.7820
  • —Auc: 0.7820

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: 5e-05
  • —trainbatchsize: 32
  • —evalbatchsize: 32
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 2

Training results

Training LossEpochStepValidation LossAccuracyF1-scorePrecisionRecallAuc
0.3441.0770.32680.86420.78140.83470.75220.7522
0.19962.01540.37300.85920.79220.80460.78200.7820

Framework versions

  • —Transformers 4.37.2
  • —Pytorch 2.1.0+cu121
  • —Datasets 2.17.0
  • —Tokenizers 0.15.1