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distilbert-finetuned-imdb

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

  • Loss: 0.2742
  • Accuracy: 0.9321

Model description

More information needed

Intended uses & limitations

The model is fine-tuned for sentiment analysis use cases. It can take a review and classify the review as 'positive' or 'negative'.

Training and evaluation data

The model is fine-tuned with the IMDB dataset which consists of 25000 training records and 25000 testing records. The model is trained and validated on all of them.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • 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
0.2686 1.0 3125 0.2484 0.9223
0.1714 2.0 6250 0.2742 0.9321

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Model size
67M params
Tensor type
F32
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Finetuned from

Dataset used to train apenev/distilbert-finetuned-imdb

Evaluation results