| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: distilbert/distilbert-base-cased-distilled-squad |
| tags: |
| - generated_from_keras_callback |
| model-index: |
| - name: Docty/question_and_answer |
| 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. --> |
|
|
| # Docty/question_and_answer |
|
|
| This model is a fine-tuned version of [distilbert/distilbert-base-cased-distilled-squad](https://huggingface.co/distilbert/distilbert-base-cased-distilled-squad) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Train Loss: 0.4095 |
| - Validation Loss: 0.6306 |
| - Epoch: 9 |
|
|
| ## 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', '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': 2e-05, 'decay_steps': 200, '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} |
| - training_precision: float32 |
|
|
| ### Training results |
|
|
| | Train Loss | Validation Loss | Epoch | |
| |:----------:|:---------------:|:-----:| |
| | 1.2112 | 0.6667 | 0 | |
| | 0.5043 | 0.6306 | 1 | |
| | 0.4089 | 0.6306 | 2 | |
| | 0.4124 | 0.6306 | 3 | |
| | 0.4204 | 0.6306 | 4 | |
| | 0.4269 | 0.6306 | 5 | |
| | 0.4218 | 0.6306 | 6 | |
| | 0.4031 | 0.6306 | 7 | |
| | 0.4117 | 0.6306 | 8 | |
| | 0.4095 | 0.6306 | 9 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.47.0 |
| - TensorFlow 2.17.1 |
| - Datasets 3.2.0 |
| - Tokenizers 0.21.0 |
|
|
