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metadata
license: mit
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: dignity-classifier-base
    results: []

dignity-classifier-base

This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6340
  • Accuracy: 0.8391

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: 5e-05
  • train_batch_size: 32
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.7117 1.0 98 0.6658 0.7328
0.4678 2.0 196 0.5435 0.7816
0.2648 3.0 294 0.5548 0.8132
0.1378 4.0 392 0.5295 0.8362
0.0561 5.0 490 0.6340 0.8391

Framework versions

  • Transformers 4.29.2
  • Pytorch 1.13.1
  • Datasets 2.12.0
  • Tokenizers 0.13.3