Edit model card

distilbert-base-uncased_allagree3

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

  • Loss: 0.0937
  • Accuracy: 0.9779
  • F1: 0.9780

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
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.6418 1.0 57 0.3340 0.8805 0.8768
0.1821 2.0 114 0.1088 0.9690 0.9691
0.0795 3.0 171 0.0822 0.9823 0.9823
0.0385 4.0 228 0.0939 0.9646 0.9646
0.0218 5.0 285 0.1151 0.9735 0.9737
0.0149 6.0 342 0.1126 0.9690 0.9694
0.006 7.0 399 0.0989 0.9779 0.9780
0.0093 8.0 456 0.1009 0.9779 0.9780
0.0063 9.0 513 0.0899 0.9779 0.9780
0.0039 10.0 570 0.0937 0.9779 0.9780

Framework versions

  • Transformers 4.17.0
  • Pytorch 1.11.0+cpu
  • Datasets 2.3.2
  • Tokenizers 0.12.1
Downloads last month
5
Hosted inference API
Text Classification
Examples
Examples
This model can be loaded on the Inference API on-demand.

Dataset used to train Farshid/distilbert-base-uncased_allagree3

Evaluation results