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bert-base-portuguese-cased_LRATE_1e-06_EPOCHS_10

Text Classification
Transformers
TensorFlow
bert
generated_from_keras_callback
Inference Endpoints
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bert-base-portuguese-cased_LRATE_1e-06_EPOCHS_10 / README.md
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metadata
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
  - generated_from_keras_callback
model-index:
  - name: gustavokpc/bert-base-portuguese-cased_LRATE_1e-06_EPOCHS_10
    results: []

gustavokpc/bert-base-portuguese-cased_LRATE_1e-06_EPOCHS_10

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

  • Train Loss: 0.1478
  • Train Accuracy: 0.9481
  • Train F1 M: 0.5518
  • Train Precision M: 0.4013
  • Train Recall M: 0.9436
  • Validation Loss: 0.1862
  • Validation Accuracy: 0.9307
  • Validation F1 M: 0.5600
  • Validation Precision M: 0.4033
  • Validation Recall M: 0.9613
  • Epoch: 9

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:

  • optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-06, 'decay_steps': 7580, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Train Accuracy Train F1 M Train Precision M Train Recall M Validation Loss Validation Accuracy Validation F1 M Validation Precision M Validation Recall M Epoch
0.4813 0.7972 0.2411 0.2093 0.3344 0.2665 0.9090 0.5217 0.3877 0.8393 0
0.2432 0.9126 0.5317 0.3942 0.8764 0.2185 0.9169 0.5490 0.3979 0.9239 1
0.2054 0.9262 0.5438 0.3981 0.9151 0.2059 0.9222 0.5441 0.3948 0.9188 2
0.1883 0.9300 0.5471 0.3992 0.9253 0.1970 0.9294 0.5504 0.3977 0.9356 3
0.1771 0.9359 0.5494 0.4011 0.9339 0.1918 0.9268 0.5550 0.4005 0.9486 4
0.1632 0.9418 0.5507 0.4016 0.9369 0.1889 0.9294 0.5578 0.4023 0.9538 5
0.1591 0.9436 0.5507 0.4023 0.9416 0.1878 0.9307 0.5547 0.4005 0.9464 6
0.1536 0.9452 0.5529 0.4028 0.9419 0.1871 0.9301 0.5561 0.4010 0.9521 7
0.1512 0.9471 0.5514 0.4012 0.9396 0.1864 0.9307 0.5599 0.4032 0.9613 8
0.1478 0.9481 0.5518 0.4013 0.9436 0.1862 0.9307 0.5600 0.4033 0.9613 9

Framework versions

  • Transformers 4.37.2
  • TensorFlow 2.15.0
  • Datasets 2.16.1
  • Tokenizers 0.15.1