| | --- |
| | license: mit |
| | tags: |
| | - generated_from_keras_callback |
| | model-index: |
| | - name: FYP2022 |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # FYP2022 |
| |
|
| | This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Train Loss: 0.6016 |
| | - Train Sparse Categorical Accuracy: 0.7503 |
| | - Train Sparse Top 3 Categorical Accuracy: 0.9901 |
| | - Epoch: 5 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## Training and evaluation data |
| |
|
| | More information needed |
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - optimizer: {'name': 'Adam', 'clipnorm': 1.0, 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False} |
| | - training_precision: float32 |
| |
|
| | ### Training results |
| |
|
| | | Train Loss | Train Sparse Categorical Accuracy | Train Sparse Top 3 Categorical Accuracy | Epoch | |
| | |:----------:|:---------------------------------:|:---------------------------------------:|:-----:| |
| | | 0.9433 | 0.5975 | 0.9523 | 0 | |
| | | 0.8257 | 0.6498 | 0.9704 | 1 | |
| | | 0.7625 | 0.6765 | 0.9778 | 2 | |
| | | 0.7062 | 0.7014 | 0.9832 | 3 | |
| | | 0.6526 | 0.7263 | 0.9872 | 4 | |
| | | 0.6016 | 0.7503 | 0.9901 | 5 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.19.2 |
| | - TensorFlow 2.8.0 |
| | - Tokenizers 0.12.1 |
| |
|
