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tweet_sentiments_analysis_bert

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

  • Loss: 0.6473
  • F1-score: 0.7199

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: 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: 5

Training results

Training Loss Epoch Step Validation Loss F1-score
0.6762 1.0 1000 0.6473 0.7199
0.537 2.0 2000 0.6577 0.7334
0.3792 3.0 3000 0.8750 0.7392
0.2142 4.0 4000 1.2328 0.7425
0.1037 5.0 5000 1.4804 0.7410

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3
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