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---
base_model: dccuchile/bert-base-spanish-wwm-uncased
tags:
- generated_from_keras_callback
model-index:
- name: RafaelMayer/bert-copec-1
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# RafaelMayer/bert-copec-1
This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-uncased](https://huggingface.co/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
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