distilbert-base-uncased-lora-text-classification

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

  • Loss: 0.4402
  • Accuracy: {'accuracy': 0.874}

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
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 250 0.4001 {'accuracy': 0.866}
0.336 2.0 500 0.4402 {'accuracy': 0.874}

Framework versions

  • Transformers 4.32.1
  • Pytorch 2.1.2+cpu
  • Datasets 2.19.2
  • Tokenizers 0.13.3
Downloads last month

-

Downloads are not tracked for this model. How to track
Inference API
Unable to determine this model's library. Check the docs .

Model tree for rinki24/distilbert-base-uncased-lora-text-classification

Finetuned
(6823)
this model