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topic_classification

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

  • Loss: 1.1769
  • Accuracy: 0.6518

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: 0.0001
  • train_batch_size: 64
  • eval_batch_size: 128
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.005 1.0 625 1.0478 0.6519
0.7717 2.0 1250 1.0482 0.6557
0.4566 3.0 1875 1.1769 0.6518

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Safetensors
Model size
109M params
Tensor type
F32
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Finetuned from

Dataset used to train Prezily/topic_classification

Evaluation results