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clasificador-glue

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

  • Loss: 1.3017
  • Accuracy: 0.6837

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: 3.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 358 0.8826 0.6084
0.6268 2.0 716 0.6036 0.7079
0.3358 3.0 1074 1.3017 0.6837

Framework versions

  • Transformers 4.30.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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Dataset used to train macampaz/clasificador-glue

Evaluation results