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--- |
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license: apache-2.0 |
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base_model: google-bert/bert-base-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: kasrahabib/bert-base-uncased-finetuned-iso29148-sward-on-promise-km-labels-nf-subclasses-cls |
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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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# kasrahabib/bert-base-uncased-finetuned-iso29148-sward-on-promise-km-labels-nf-subclasses-cls |
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This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-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: 0.0007 |
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- Validation Loss: 1.0381 |
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- Epoch: 14 |
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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', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 123615, '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} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Epoch | |
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|:----------:|:---------------:|:-----:| |
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| 0.7510 | 0.5526 | 0 | |
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| 0.3329 | 0.5541 | 1 | |
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| 0.1715 | 0.6226 | 2 | |
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| 0.1029 | 0.6412 | 3 | |
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| 0.0699 | 0.7550 | 4 | |
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| 0.0500 | 0.7140 | 5 | |
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| 0.0372 | 0.7635 | 6 | |
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| 0.0250 | 0.8047 | 7 | |
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| 0.0205 | 0.8339 | 8 | |
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| 0.0126 | 0.8673 | 9 | |
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| 0.0096 | 0.9238 | 10 | |
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| 0.0068 | 0.9350 | 11 | |
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| 0.0029 | 1.0098 | 12 | |
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| 0.0016 | 1.0402 | 13 | |
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| 0.0007 | 1.0381 | 14 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- TensorFlow 2.15.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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