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---
license: apache-2.0
base_model: bert-large-uncased
tags:
- generated_from_keras_callback
model-index:
- name: gustavokpc/IC_11
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. -->
# gustavokpc/IC_11
This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.1200
- Train Accuracy: 0.9569
- Train F1 M: 0.5414
- Train Precision M: 0.3981
- Train Recall M: 0.9034
- Validation Loss: 0.2290
- Validation Accuracy: 0.9202
- Validation F1 M: 0.5513
- Validation Precision M: 0.4022
- Validation Recall M: 0.9261
- Epoch: 6
## 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': 5e-06, 'decay_steps': 5306, '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 |
|:----------:|:--------------:|:----------:|:-----------------:|:--------------:|:---------------:|:-------------------:|:---------------:|:----------------------:|:-------------------:|:-----:|
| 0.4434 | 0.8014 | 0.4236 | 0.3661 | 0.5865 | 0.2743 | 0.8872 | 0.4964 | 0.3787 | 0.7644 | 0 |
| 0.2804 | 0.8901 | 0.4898 | 0.3778 | 0.7488 | 0.2824 | 0.8879 | 0.5567 | 0.4181 | 0.8782 | 1 |
| 0.2254 | 0.9128 | 0.5069 | 0.3838 | 0.8028 | 0.2388 | 0.9090 | 0.5468 | 0.4009 | 0.9053 | 2 |
| 0.1873 | 0.9303 | 0.5203 | 0.3889 | 0.8490 | 0.2200 | 0.9149 | 0.5561 | 0.4075 | 0.9235 | 3 |
| 0.1614 | 0.9404 | 0.5316 | 0.3944 | 0.8756 | 0.2188 | 0.9235 | 0.5566 | 0.4080 | 0.9242 | 4 |
| 0.1380 | 0.9497 | 0.5359 | 0.3956 | 0.8898 | 0.2205 | 0.9228 | 0.5506 | 0.4024 | 0.9213 | 5 |
| 0.1200 | 0.9569 | 0.5414 | 0.3981 | 0.9034 | 0.2290 | 0.9202 | 0.5513 | 0.4022 | 0.9261 | 6 |
### Framework versions
- Transformers 4.34.1
- TensorFlow 2.14.0
- Datasets 2.14.5
- Tokenizers 0.14.1
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