| license: apache-2.0 | |
| tags: | |
| - generated_from_keras_callback | |
| model-index: | |
| - name: dosai/distilbert-sud | |
| 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. --> | |
| # dosai/distilbert-sud | |
| This model is a fine-tuned version of [distilbert-base-cased-distilled-squad](https://huggingface.co/distilbert-base-cased-distilled-squad) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Train Loss: 0.0026 | |
| - Epoch: 29 | |
| ## 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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 40440, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.001} | |
| - training_precision: mixed_float16 | |
| ### Training results | |
| | Train Loss | Epoch | | |
| |:----------:|:-----:| | |
| | 0.5392 | 0 | | |
| | 0.2639 | 1 | | |
| | 0.1945 | 2 | | |
| | 0.1562 | 3 | | |
| | 0.1274 | 4 | | |
| | 0.1065 | 5 | | |
| | 0.0871 | 6 | | |
| | 0.0714 | 7 | | |
| | 0.0598 | 8 | | |
| | 0.0499 | 9 | | |
| | 0.0436 | 10 | | |
| | 0.0376 | 11 | | |
| | 0.0305 | 12 | | |
| | 0.0286 | 13 | | |
| | 0.0223 | 14 | | |
| | 0.0215 | 15 | | |
| | 0.0210 | 16 | | |
| | 0.0139 | 17 | | |
| | 0.0147 | 18 | | |
| | 0.0119 | 19 | | |
| | 0.0091 | 20 | | |
| | 0.0086 | 21 | | |
| | 0.0077 | 22 | | |
| | 0.0055 | 23 | | |
| | 0.0060 | 24 | | |
| | 0.0047 | 25 | | |
| | 0.0039 | 26 | | |
| | 0.0037 | 27 | | |
| | 0.0028 | 28 | | |
| | 0.0026 | 29 | | |
| ### Framework versions | |
| - Transformers 4.29.2 | |
| - TensorFlow 2.12.0 | |
| - Datasets 2.12.0 | |
| - Tokenizers 0.13.3 | |