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metadata
license: mit
base_model: PORTULAN/albertina-100m-portuguese-ptpt-encoder
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: LVI_albertina-100m-portuguese-ptpt-encoder
    results: []

LVI_albertina-100m-portuguese-ptpt-encoder

This model is a fine-tuned version of PORTULAN/albertina-100m-portuguese-ptpt-encoder on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1867
  • Accuracy: 0.9802
  • F1: 0.9800
  • Precision: 0.9905
  • Recall: 0.9696

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-06
  • 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: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
0.1284 1.0 3217 0.1454 0.9581 0.9567 0.9882 0.9272
0.0946 2.0 6434 0.1211 0.9737 0.9734 0.9864 0.9607
0.0575 3.0 9651 0.1087 0.9776 0.9774 0.9892 0.9659
0.0374 4.0 12868 0.1033 0.981 0.9809 0.9854 0.9765
0.0311 5.0 16085 0.1154 0.981 0.9808 0.9896 0.9722
0.0125 6.0 19302 0.1143 0.9830 0.9830 0.9833 0.9826
0.0107 7.0 22519 0.1562 0.9807 0.9805 0.9910 0.9702
0.0032 8.0 25736 0.1711 0.9808 0.9806 0.9892 0.9721
0.0036 9.0 28953 0.1867 0.9802 0.9800 0.9905 0.9696

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2