| | ---
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| | library_name: transformers
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| | license: apache-2.0
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| | base_model: distilbert/distilbert-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: Fake_News_Bert_Model2
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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
|
| | probably proofread and complete it, then remove this comment. -->
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| |
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| | # Fake_News_Bert_Model2
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| |
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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: 0.2787
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| | - Train Accuracy: 0.9062
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| | - Validation Loss: 0.3022
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| | - Validation Accuracy: 0.8774
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| | - Epoch: 2
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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': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2110, '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 | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
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| | |:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
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| | | 0.6032 | 0.6178 | 0.4880 | 0.7170 | 0 |
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| | | 0.4076 | 0.8606 | 0.3893 | 0.8396 | 1 |
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| | | 0.2787 | 0.9062 | 0.3022 | 0.8774 | 2 |
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| |
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| |
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| | ### Framework versions
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| |
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| | - Transformers 4.45.2
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| | - TensorFlow 2.16.2
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| | - Datasets 3.0.1
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| | - Tokenizers 0.20.1
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| | |
