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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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datasets: |
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- disfl_qa |
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metrics: |
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- validation_accuracy |
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model-index: |
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- name: fintuned-bert-disfluency |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: disfl_qa |
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type: disfl_qa |
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args: disfl_qa |
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metrics: |
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- name: Validation Accuracy |
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type: validation_accuracy |
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value: 0.9795 |
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widget: |
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- text: "I love football so much" |
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example_title: "Non Disfluent" |
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- text: "I love love football I like it" |
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example_title: "Disfluent" |
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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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# fintuned-bert-disfluency |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/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: 0.0814 |
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- Train Sparse Categorical Accuracy: 0.9795 |
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- Validation Loss: 0.0816 |
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- Validation Sparse Categorical Accuracy: 0.9795 |
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- Epoch: 2 |
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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': 5e-05, 'decay': 0.0, '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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| Train Loss | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch | |
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|:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:| |
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| 0.1105 | 0.9694 | 0.0821 | 0.9800 | 0 | |
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| 0.0942 | 0.9759 | 0.0987 | 0.9765 | 1 | |
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| 0.0814 | 0.9795 | 0.0816 | 0.9795 | 2 | |
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### Framework versions |
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- Transformers 4.21.3 |
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- TensorFlow 2.8.2 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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