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fine_tuned_boolq_bert_croslo

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

  • Loss: 1.3270
  • Accuracy: 0.8333
  • F1: 0.8243

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • training_steps: 400

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.5567 4.1667 50 0.5262 0.7222 0.6523
0.1098 8.3333 100 0.8949 0.8333 0.8243
0.0031 12.5 150 1.2237 0.7778 0.7778
0.0011 16.6667 200 1.2641 0.7778 0.7778
0.0008 20.8333 250 1.2343 0.8333 0.8243
0.0007 25.0 300 1.2852 0.8333 0.8243
0.0005 29.1667 350 1.3133 0.8333 0.8243
0.0005 33.3333 400 1.3270 0.8333 0.8243

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.3.0
  • Datasets 2.19.0
  • Tokenizers 0.19.1
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