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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: Electro98/my_awesome_model_v2 |
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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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# Electro98/my_awesome_model_v2 |
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This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.1620 |
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- Validation Loss: 0.1617 |
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- Train F1: 0.0731 |
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- Train Accuracy: 0.1217 |
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- Epoch: 12 |
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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': 1056100, '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 | Validation Loss | Train F1 | Train Accuracy | Epoch | |
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|:----------:|:---------------:|:--------:|:--------------:|:-----:| |
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| 0.1841 | 0.1586 | 0.0441 | 0.0484 | 0 | |
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| 0.1733 | 0.1553 | 0.0447 | 0.0537 | 1 | |
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| 0.1628 | 0.1516 | 0.0757 | 0.0990 | 2 | |
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| 0.1600 | 0.1559 | 0.0700 | 0.1263 | 3 | |
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| 0.1634 | 0.1549 | 0.0662 | 0.0956 | 4 | |
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| 0.1620 | 0.1526 | 0.0611 | 0.0777 | 5 | |
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| 0.1622 | 0.1718 | 0.0809 | 0.0865 | 6 | |
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| 0.1625 | 0.1577 | 0.0498 | 0.0942 | 7 | |
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| 0.1649 | 0.1566 | 0.0799 | 0.1404 | 8 | |
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| 0.1684 | 0.1585 | 0.0700 | 0.1262 | 9 | |
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| 0.1628 | 0.1582 | 0.0802 | 0.1112 | 10 | |
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| 0.1605 | 0.1614 | 0.0651 | 0.1065 | 11 | |
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| 0.1620 | 0.1617 | 0.0731 | 0.1217 | 12 | |
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### Framework versions |
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- Transformers 4.27.4 |
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- TensorFlow 2.10.0 |
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- Datasets 2.18.0 |
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- Tokenizers 0.13.3 |
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