CoolFace
Modelpublic

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

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
0likes7downloads
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: 0.9490
  • —Accuracy: {'accuracy': 0.896}

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 10

Training results

Training LossEpochStepValidation LossAccuracy
No log1.02500.4908{'accuracy': 0.865}
0.42382.05000.3895{'accuracy': 0.884}
0.42383.07500.7152{'accuracy': 0.878}
0.18774.010000.6360{'accuracy': 0.898}
0.18775.012500.7666{'accuracy': 0.897}
0.08056.015000.8102{'accuracy': 0.891}
0.08057.017500.8150{'accuracy': 0.89}
0.02838.020000.9224{'accuracy': 0.893}
0.02839.022500.9227{'accuracy': 0.894}
0.014810.025000.9490{'accuracy': 0.896}

Framework versions

  • —PEFT 0.10.0
  • —Transformers 4.39.3
  • —Pytorch 2.2.2+cu121
  • —Datasets 2.18.0
  • —Tokenizers 0.15.2