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finetuning-sentiment-model-1000-samples

This model is a fine-tuned version of finiteautomata/bertweet-base-sentiment-analysis on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0961
  • Accuracy: {'accuracy': 0.9825}
  • F1: 0.9831

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2

Training results

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cpu
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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