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RafaelMayer
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bert-copec-1

Text Classification
Transformers
TensorFlow
bert
generated_from_keras_callback
Inference Endpoints
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bert-copec-1 / README.md
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metadata
base_model: dccuchile/bert-base-spanish-wwm-uncased
tags:
  - generated_from_keras_callback
model-index:
  - name: RafaelMayer/bert-copec-1
    results: []

RafaelMayer/bert-copec-1

This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 0.1258
  • Validation Loss: 0.4666
  • Train Accuracy: 0.7647
  • Train Precision: [0. 0.8125]
  • Train Precision W: 0.6691
  • Train Recall: [0. 0.92857143]
  • Train Recall W: 0.7647
  • Train F1: [0. 0.86666667]
  • Train F1 W: 0.7137
  • 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': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 35, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'passive_serialization': True}, 'warmup_steps': 5, 'power': 1.0, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Validation Loss Train Accuracy Train Precision Train Precision W Train Recall Train Recall W Train F1 Train F1 W Epoch
0.5926 0.4830 0.8235 [0. 0.82352941] 0.6782 [0. 1.] 0.8235 [0. 0.90322581] 0.7438 1
0.3224 0.5166 0.8235 [0. 0.82352941] 0.6782 [0. 1.] 0.8235 [0. 0.90322581] 0.7438 2
0.2419 0.6137 0.8235 [0. 0.82352941] 0.6782 [0. 1.] 0.8235 [0. 0.90322581] 0.7438 3
0.2583 0.5984 0.8235 [0. 0.82352941] 0.6782 [0. 1.] 0.8235 [0. 0.90322581] 0.7438 4
0.2308 0.5345 0.8235 [0. 0.82352941] 0.6782 [0. 1.] 0.8235 [0. 0.90322581] 0.7438 5
0.2178 0.4710 0.8235 [0. 0.82352941] 0.6782 [0. 1.] 0.8235 [0. 0.90322581] 0.7438 6
0.1861 0.4562 0.8235 [0. 0.82352941] 0.6782 [0. 1.] 0.8235 [0. 0.90322581] 0.7438 7
0.1456 0.4568 0.7647 [0. 0.8125] 0.6691 [0. 0.92857143] 0.7647 [0. 0.86666667] 0.7137 8
0.1258 0.4666 0.7647 [0. 0.8125] 0.6691 [0. 0.92857143] 0.7647 [0. 0.86666667] 0.7137 9

Framework versions

  • Transformers 4.32.1
  • TensorFlow 2.12.0
  • Datasets 2.14.4
  • Tokenizers 0.13.3