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transformers-qa-kaggle-tpu
This model is a fine-tuned version of distilbert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.2278
- Train End Logits Accuracy: 0.9244
- Train Start Logits Accuracy: 0.9207
- Validation Loss: 3.8999
- Validation End Logits Accuracy: 0.4812
- Validation Start Logits Accuracy: 0.4542
- Epoch: 14
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': False, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 122160, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
|---|---|---|---|---|---|---|
| 2.2837 | 0.4519 | 0.4182 | 2.1117 | 0.4890 | 0.4658 | 0 |
| 1.7361 | 0.5642 | 0.5326 | 2.0268 | 0.5035 | 0.4788 | 1 |
| 1.4664 | 0.6186 | 0.5893 | 2.0023 | 0.5093 | 0.4833 | 2 |
| 1.2479 | 0.6661 | 0.6379 | 2.1252 | 0.5057 | 0.4744 | 3 |
| 1.0596 | 0.7076 | 0.6832 | 2.2703 | 0.4975 | 0.4690 | 4 |
| 0.8999 | 0.7434 | 0.7214 | 2.3834 | 0.4968 | 0.4714 | 5 |
| 0.7661 | 0.7760 | 0.7557 | 2.5503 | 0.4906 | 0.4654 | 6 |
| 0.6520 | 0.8042 | 0.7892 | 2.7740 | 0.4922 | 0.4540 | 7 |
| 0.5549 | 0.8313 | 0.8156 | 3.0625 | 0.4884 | 0.4607 | 8 |
| 0.4739 | 0.8512 | 0.8405 | 3.1365 | 0.4862 | 0.4535 | 9 |
| 0.4072 | 0.8691 | 0.8620 | 3.2969 | 0.4830 | 0.4509 | 10 |
| 0.3515 | 0.8863 | 0.8786 | 3.4301 | 0.4852 | 0.4530 | 11 |
| 0.3025 | 0.9010 | 0.8954 | 3.5350 | 0.4814 | 0.4548 | 12 |
| 0.2646 | 0.9127 | 0.9083 | 3.7923 | 0.4832 | 0.4539 | 13 |
| 0.2278 | 0.9244 | 0.9207 | 3.8999 | 0.4812 | 0.4542 | 14 |
Framework versions
- Transformers 4.31.0.dev0
- TensorFlow 2.12.0
- Datasets 2.13.1
- Tokenizers 0.13.3
