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dosai/berts-finetuned-squad
This model is a fine-tuned version of bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0077
- 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: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1020, '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}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
- training_precision: mixed_float16
Training results
| Train Loss | Epoch |
|---|---|
| 3.6463 | 0 |
| 1.7361 | 1 |
| 1.2498 | 2 |
| 0.8598 | 3 |
| 0.7020 | 4 |
| 0.3977 | 5 |
| 0.2314 | 6 |
| 0.1092 | 7 |
| 0.0666 | 8 |
| 0.0521 | 9 |
| 0.0412 | 10 |
| 0.0354 | 11 |
| 0.0269 | 12 |
| 0.0177 | 13 |
| 0.0184 | 14 |
| 0.0369 | 15 |
| 0.0198 | 16 |
| 0.0169 | 17 |
| 0.0132 | 18 |
| 0.0091 | 19 |
| 0.0080 | 20 |
| 0.0093 | 21 |
| 0.0065 | 22 |
| 0.0064 | 23 |
| 0.0108 | 24 |
| 0.0080 | 25 |
| 0.0070 | 26 |
| 0.0071 | 27 |
| 0.0061 | 28 |
| 0.0077 | 29 |
Framework versions
- Transformers 4.29.2
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3
