| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_keras_callback |
| model-index: |
| - name: LovenOO/distilBERT_without_preprocessing |
| 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. --> |
|
|
| # LovenOO/distilBERT_without_preprocessing |
|
|
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Train Loss: 0.1466 |
| - Validation Loss: 0.3625 |
| - Train Precision: 0.8491 |
| - Train Recall: 0.8642 |
| - Train F1: 0.8544 |
| - Train Accuracy: 0.8906 |
| - 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', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2565, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False} |
| - training_precision: float32 |
| |
| ### Training results |
| |
| | Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch | |
| |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:| |
| | 0.8177 | 0.4723 | 0.8407 | 0.7879 | 0.7948 | 0.8575 | 0 | |
| | 0.3642 | 0.3777 | 0.8666 | 0.8315 | 0.8465 | 0.8847 | 1 | |
| | 0.2734 | 0.3804 | 0.8466 | 0.8563 | 0.8471 | 0.8872 | 2 | |
| | 0.2020 | 0.3704 | 0.8526 | 0.8663 | 0.8551 | 0.8896 | 3 | |
| | 0.1638 | 0.3625 | 0.8491 | 0.8642 | 0.8544 | 0.8906 | 4 | |
| | 0.1466 | 0.3625 | 0.8491 | 0.8642 | 0.8544 | 0.8906 | 5 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.24.0 |
| - TensorFlow 2.13.0 |
| - Datasets 2.14.2 |
| - Tokenizers 0.11.0 |
| |
