metadata
license: apache-2.0
base_model: bert-large-uncased
tags:
- generated_from_keras_callback
model-index:
- name: vedantjumle/bert-2
results: []
vedantjumle/bert-2
This model is a fine-tuned version of bert-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 4.4459
- Validation Loss: 4.3669
- Train Accuracy: 0.0233
- Epoch: 25
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': 6000, '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 | Train Accuracy | Epoch |
|---|---|---|---|
| 5.1229 | 5.0343 | 0.0067 | 0 |
| 5.0629 | 5.0547 | 0.0033 | 1 |
| 5.0585 | 5.0239 | 0.0167 | 2 |
| 5.0530 | 5.0257 | 0.0167 | 3 |
| 5.0545 | 5.0207 | 0.01 | 4 |
| 5.0549 | 5.0104 | 0.01 | 5 |
| 5.0401 | 5.0240 | 0.0067 | 6 |
| 5.0400 | 5.0121 | 0.01 | 7 |
| 5.0372 | 5.0030 | 0.0167 | 8 |
| 5.0326 | 5.0256 | 0.0067 | 9 |
| 5.0382 | 4.9992 | 0.01 | 10 |
| 5.0144 | 4.9976 | 0.01 | 11 |
| 5.0152 | 4.9783 | 0.0167 | 12 |
| 4.9700 | 4.9433 | 0.0067 | 13 |
| 4.9206 | 4.9482 | 0.0067 | 14 |
| 4.9153 | 4.8727 | 0.0067 | 15 |
| 4.9287 | 4.7980 | 0.0167 | 16 |
| 4.8014 | 4.7452 | 0.0167 | 17 |
| 4.7477 | 4.6429 | 0.01 | 18 |
| 4.6939 | 4.6035 | 0.02 | 19 |
| 4.6607 | 4.5406 | 0.02 | 20 |
| 4.6075 | 4.5490 | 0.0167 | 21 |
| 4.5748 | 4.5086 | 0.0333 | 22 |
| 4.5383 | 4.3940 | 0.0333 | 23 |
| 4.4965 | 4.3748 | 0.0233 | 24 |
| 4.4459 | 4.3669 | 0.0233 | 25 |
Framework versions
- Transformers 4.34.0
- TensorFlow 2.13.0
- Datasets 2.14.5
- Tokenizers 0.14.1