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AdeshJha1101/it-support-model

sourceHugging Faceapache-2.0updated 2d agoView on Hugging Face
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it-support-model

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

  • Loss: 1.2334
  • Accuracy: 0.4
  • Precision: 0.4667
  • Recall: 0.4
  • F1: 0.3667

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: 8
  • 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
  • num_epochs: 10
  • mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracyPrecisionRecallF1
No log1.031.37870.20.040.20.0667
1.38382.061.36560.40.450.40.3467
1.38383.091.34980.60.60.60.5333
1.33774.0121.33050.40.450.40.3467
1.24415.0151.30960.40.450.40.3467
1.24416.0181.28670.40.450.40.3467
1.15277.0211.26640.40.46670.40.3667
1.15278.0241.24940.40.46670.40.3667
1.14189.0271.23800.40.46670.40.3667
1.068310.0301.23340.40.46670.40.3667

Framework versions

  • Transformers 5.17.0
  • Pytorch 2.11.0+cu128
  • Datasets 5.0.1
  • Tokenizers 0.23.1