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EricPeter/distilbert-base-cased
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.2356
- Epoch: 49
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': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2846, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'passive_serialization': True}, 'warmup_steps': 4, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.06}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
- training_precision: mixed_float16
Training results
| Train Loss | Epoch |
|---|---|
| 0.3158 | 0 |
| 0.3561 | 1 |
| 0.2694 | 2 |
| 0.2718 | 3 |
| 0.2687 | 4 |
| 0.2844 | 5 |
| 0.2824 | 6 |
| 0.2698 | 7 |
| 0.2882 | 8 |
| 0.2808 | 9 |
| 0.2710 | 10 |
| 0.2663 | 11 |
| 0.2574 | 12 |
| 0.2417 | 13 |
| 0.2581 | 14 |
| 0.2581 | 15 |
| 0.2625 | 16 |
| 0.2443 | 17 |
| 0.2360 | 18 |
| 0.2478 | 19 |
| 0.2431 | 20 |
| 0.2454 | 21 |
| 0.2409 | 22 |
| 0.2359 | 23 |
| 0.2428 | 24 |
| 0.2374 | 25 |
| 0.2419 | 26 |
| 0.2371 | 27 |
| 0.2392 | 28 |
| 0.2393 | 29 |
| 0.2378 | 30 |
| 0.2399 | 31 |
| 0.2381 | 32 |
| 0.2347 | 33 |
| 0.2414 | 34 |
| 0.2352 | 35 |
| 0.2361 | 36 |
| 0.2407 | 37 |
| 0.2397 | 38 |
| 0.2314 | 39 |
| 0.2370 | 40 |
| 0.2338 | 41 |
| 0.2360 | 42 |
| 0.2356 | 43 |
| 0.2375 | 44 |
| 0.2343 | 45 |
| 0.2366 | 46 |
| 0.2377 | 47 |
| 0.2369 | 48 |
| 0.2356 | 49 |
Framework versions
- Transformers 4.32.0
- TensorFlow 2.12.0
- Datasets 2.14.4
- Tokenizers 0.13.3
