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--- |
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license: apache-2.0 |
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base_model: bert-large-uncased |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: gustavokpc/IC_sexto |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# gustavokpc/IC_sexto |
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This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.0832 |
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- Train Accuracy: 0.9695 |
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- Train F1 M: 0.5509 |
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- Train Precision M: 0.4007 |
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- Train Recall M: 0.9444 |
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- Validation Loss: 0.2387 |
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- Validation Accuracy: 0.9248 |
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- Validation F1 M: 0.5604 |
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- Validation Precision M: 0.4074 |
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- Validation Recall M: 0.9461 |
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- Epoch: 4 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- 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} |
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- training_precision: float32 |
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### Training results |
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| 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 | |
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|:----------:|:--------------:|:----------:|:-----------------:|:--------------:|:---------------:|:-------------------:|:---------------:|:----------------------:|:-------------------:|:-----:| |
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| 0.3898 | 0.8294 | 0.3411 | 0.2894 | 0.4810 | 0.2440 | 0.8984 | 0.5087 | 0.3814 | 0.8079 | 0 | |
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| 0.2070 | 0.9228 | 0.4927 | 0.3723 | 0.7869 | 0.1911 | 0.9268 | 0.5222 | 0.3853 | 0.8520 | 1 | |
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| 0.1392 | 0.9467 | 0.5266 | 0.3881 | 0.8670 | 0.2310 | 0.9057 | 0.5617 | 0.4162 | 0.9092 | 2 | |
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| 0.1136 | 0.9570 | 0.5387 | 0.3946 | 0.9100 | 0.2265 | 0.9228 | 0.5653 | 0.4119 | 0.9501 | 3 | |
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| 0.0832 | 0.9695 | 0.5509 | 0.4007 | 0.9444 | 0.2387 | 0.9248 | 0.5604 | 0.4074 | 0.9461 | 4 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- TensorFlow 2.10.0 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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