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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: FacebookAI/roberta-base
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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/roberta-base-finetuned-iso29148-promise-km-labels-nf-subclasses-cls
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+ results: []
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+ ---
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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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+
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+ # kasrahabib/roberta-base-finetuned-iso29148-promise-km-labels-nf-subclasses-cls
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+
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+ This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Train Loss: 0.0124
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+ - Validation Loss: 0.1623
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+ - Epoch: 29
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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': 1770, '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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+
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+ ### Training results
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+
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+ | Train Loss | Validation Loss | Epoch |
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+ |:----------:|:---------------:|:-----:|
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+ | 2.1848 | 1.7407 | 0 |
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+ | 1.2611 | 0.8464 | 1 |
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+ | 0.5377 | 0.4928 | 2 |
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+ | 0.2843 | 0.2790 | 3 |
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+ | 0.1531 | 0.3657 | 4 |
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+ | 0.1186 | 0.1997 | 5 |
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+ | 0.0646 | 0.1742 | 6 |
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+ | 0.0498 | 0.1731 | 7 |
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+ | 0.0417 | 0.1709 | 8 |
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+ | 0.0351 | 0.1689 | 9 |
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+ | 0.0309 | 0.1659 | 10 |
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+ | 0.0270 | 0.1674 | 11 |
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+ | 0.0255 | 0.1687 | 12 |
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+ | 0.0229 | 0.1665 | 13 |
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+ | 0.0210 | 0.1673 | 14 |
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+ | 0.0193 | 0.1677 | 15 |
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+ | 0.0185 | 0.1664 | 16 |
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+ | 0.0168 | 0.1658 | 17 |
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+ | 0.0162 | 0.1649 | 18 |
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+ | 0.0156 | 0.1670 | 19 |
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+ | 0.0150 | 0.1678 | 20 |
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+ | 0.0144 | 0.1656 | 21 |
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+ | 0.0141 | 0.1653 | 22 |
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+ | 0.0138 | 0.1662 | 23 |
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+ | 0.0132 | 0.1668 | 24 |
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+ | 0.0127 | 0.1629 | 25 |
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+ | 0.0125 | 0.1614 | 26 |
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+ | 0.0123 | 0.1619 | 27 |
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+ | 0.0122 | 0.1624 | 28 |
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+ | 0.0124 | 0.1623 | 29 |
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+
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+
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+ ### Framework versions
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+
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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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