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---
license: apache-2.0
base_model: bert-large-uncased
tags:
- generated_from_keras_callback
model-index:
- name: gustavokpc/IC_sexto
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_sexto
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: 0.0832
- Train Accuracy: 0.9695
- Train F1 M: 0.5509
- Train Precision M: 0.4007
- Train Recall M: 0.9444
- Validation Loss: 0.2387
- Validation Accuracy: 0.9248
- Validation F1 M: 0.5604
- Validation Precision M: 0.4074
- Validation Recall M: 0.9461
- Epoch: 4
## 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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 3790, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, '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 |
|:----------:|:--------------:|:----------:|:-----------------:|:--------------:|:---------------:|:-------------------:|:---------------:|:----------------------:|:-------------------:|:-----:|
| 0.3898 | 0.8294 | 0.3411 | 0.2894 | 0.4810 | 0.2440 | 0.8984 | 0.5087 | 0.3814 | 0.8079 | 0 |
| 0.2070 | 0.9228 | 0.4927 | 0.3723 | 0.7869 | 0.1911 | 0.9268 | 0.5222 | 0.3853 | 0.8520 | 1 |
| 0.1392 | 0.9467 | 0.5266 | 0.3881 | 0.8670 | 0.2310 | 0.9057 | 0.5617 | 0.4162 | 0.9092 | 2 |
| 0.1136 | 0.9570 | 0.5387 | 0.3946 | 0.9100 | 0.2265 | 0.9228 | 0.5653 | 0.4119 | 0.9501 | 3 |
| 0.0832 | 0.9695 | 0.5509 | 0.4007 | 0.9444 | 0.2387 | 0.9248 | 0.5604 | 0.4074 | 0.9461 | 4 |
### Framework versions
- Transformers 4.34.1
- TensorFlow 2.10.0
- Datasets 2.14.5
- Tokenizers 0.14.1
|