metadata
library_name: transformers
license: mit
base_model: Labira/LabiraPJOK_2_100_Full
tags:
- generated_from_keras_callback
model-index:
- name: Labira/LabiraPJOK_3_100_Full
results: []
Labira/LabiraPJOK_3_100_Full
This model is a fine-tuned version of Labira/LabiraPJOK_2_100_Full on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0091
- Validation Loss: 0.0018
- 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': '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': 1100, '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 | Epoch |
---|---|---|
2.7614 | 1.1522 | 0 |
1.5531 | 0.5524 | 1 |
1.0482 | 0.2232 | 2 |
0.5443 | 0.0847 | 3 |
0.5227 | 0.0529 | 4 |
0.2873 | 0.0412 | 5 |
0.2568 | 0.0330 | 6 |
0.1310 | 0.0190 | 7 |
0.1108 | 0.0067 | 8 |
0.1252 | 0.0117 | 9 |
0.0740 | 0.0071 | 10 |
0.0507 | 0.0059 | 11 |
0.0790 | 0.0058 | 12 |
0.0282 | 0.0036 | 13 |
0.0562 | 0.0070 | 14 |
0.0850 | 0.0047 | 15 |
0.0715 | 0.0176 | 16 |
0.0724 | 0.0077 | 17 |
0.0361 | 0.0024 | 18 |
0.0266 | 0.0029 | 19 |
0.0207 | 0.0026 | 20 |
0.0158 | 0.0023 | 21 |
0.0086 | 0.0016 | 22 |
0.0214 | 0.0093 | 23 |
0.0327 | 0.0063 | 24 |
0.0102 | 0.0016 | 25 |
0.0072 | 0.0012 | 26 |
0.0273 | 0.0024 | 27 |
0.0185 | 0.0034 | 28 |
0.0091 | 0.0018 | 29 |
Framework versions
- Transformers 4.46.2
- TensorFlow 2.17.0
- Datasets 3.1.0
- Tokenizers 0.20.3