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distilbert-base-uncasedv1-finetuned-twitter-sentiment

This model is a fine-tuned version of distilbert-base-uncased on the sentiment140 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3985
  • Accuracy: 0.8247
  • F1: 0.8246
  • Precision: 0.8251
  • Recall: 0.8017

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: 64
  • eval_batch_size: 64
  • 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 F1 Precision Recall
No log 1.0 500 0.4049 0.8181 0.8178 0.8236 0.7862
No log 2.0 1000 0.3985 0.8247 0.8246 0.8251 0.8017

Framework versions

  • Transformers 4.22.2
  • Pytorch 1.12.1+cu113
  • Datasets 2.5.2
  • Tokenizers 0.12.1
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Dataset used to train macildur/distilbert-base-uncasedv1-finetuned-twitter-sentiment

Evaluation results