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--- |
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license: apache-2.0 |
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base_model: 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: bert-base-uncased-finetuned-glue-sst2 |
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results: [] |
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--- |
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# bert-base-uncased-finetuned-glue-sst2 |
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Use for **sentiment analysis**. |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the [glue sst2 dataset](https://huggingface.co/datasets/glue/viewer/sst2). The model achieves `91.39%` accuracy on the validation dataset. |
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## Model description |
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[bert-base-uncased](https://huggingface.co/bert-base-uncased) is a pretrained English language model. `bert-base-uncased-finetuned-glue-sst2` adds a 2-class classification head for predicting `positive` and `negative` sentiment. |
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## Training and evaluation data |
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The model has been trained on 10K training samples, even though the [glue sst2 dataset](https://huggingface.co/datasets/glue/viewer/sst2) contains 67.3K samples. This was done to decrease training time. |
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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': 5e-05, 'decay_steps': 3750, '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-07, 'amsgrad': False} |
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- training_precision: float32 |
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### Training results |
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- Accuracy (training): `94.33%` |
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- Accuracy (validation): `91.39%` |
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### Framework versions |
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- Transformers 4.35.2 |
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- TensorFlow 2.15.0 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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