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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_setimo |
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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_setimo |
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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: 0.1339 |
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- Train Accuracy: 0.9523 |
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- Train F1 M: 0.5559 |
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- Train Precision M: 0.4041 |
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- Train Recall M: 0.9513 |
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- Validation Loss: 0.2110 |
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- Validation Accuracy: 0.9222 |
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- Validation F1 M: 0.5681 |
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- Validation Precision M: 0.4137 |
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- Validation Recall M: 0.9574 |
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- Epoch: 2 |
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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': 2274, '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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| 0.4176 | 0.8080 | 0.4543 | 0.3667 | 0.6857 | 0.2600 | 0.8991 | 0.5567 | 0.4108 | 0.9084 | 0 | |
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| 0.2122 | 0.9203 | 0.5400 | 0.3991 | 0.8908 | 0.2049 | 0.9215 | 0.5529 | 0.4068 | 0.9089 | 1 | |
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| 0.1339 | 0.9523 | 0.5559 | 0.4041 | 0.9513 | 0.2110 | 0.9222 | 0.5681 | 0.4137 | 0.9574 | 2 | |
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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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