CoolFace
Modelpublic

Prajapat/distilbert-base-uncased-lora-text-classification

sourceHugging Faceapache-2.0updated 8mo agoView on Hugging Face
0likes11downloads
Model Card

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

distilbert-base-uncased-lora-text-classification

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 1.0503
  • —Accuracy: {'accuracy': 0.888}

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: 0.001
  • —trainbatchsize: 4
  • —evalbatchsize: 4
  • —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 LossAccuracy
No log1.02500.5703{'accuracy': 0.841}
0.4162.05000.3604{'accuracy': 0.889}
0.4163.07500.6394{'accuracy': 0.884}
0.19014.010000.7093{'accuracy': 0.885}
0.19015.012500.7750{'accuracy': 0.885}
0.0446.015000.9100{'accuracy': 0.888}
0.0447.017501.0710{'accuracy': 0.887}
0.01518.020001.0063{'accuracy': 0.888}
0.01519.022501.0483{'accuracy': 0.892}
0.010710.025001.0503{'accuracy': 0.888}

Framework versions

  • —PEFT 0.18.1
  • —Transformers 4.57.6
  • —Pytorch 2.9.0+cu126
  • —Datasets 4.0.0
  • —Tokenizers 0.22.2