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: 0.0019
- Validation Loss: 0.0005
- Epoch: 98
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 |
| 0.0144 | 0.0021 | 30 |
| 0.0107 | 0.0032 | 31 |
| 0.0632 | 0.0037 | 32 |
| 0.0149 | 0.0034 | 33 |
| 0.0151 | 0.0103 | 34 |
| 0.0195 | 0.0081 | 35 |
| 0.0145 | 0.0023 | 36 |
| 0.0150 | 0.0012 | 37 |
| 0.0126 | 0.0018 | 38 |
| 0.0068 | 0.0017 | 39 |
| 0.0057 | 0.0014 | 40 |
| 0.0075 | 0.0015 | 41 |
| 0.0035 | 0.0015 | 42 |
| 0.0059 | 0.0013 | 43 |
| 0.0040 | 0.0010 | 44 |
| 0.0036 | 0.0009 | 45 |
| 0.0040 | 0.0011 | 46 |
| 0.0058 | 0.0020 | 47 |
| 0.0801 | 0.0013 | 48 |
| 0.0062 | 0.0014 | 49 |
| 0.0049 | 0.0011 | 50 |
| 0.0057 | 0.0012 | 51 |
| 0.0023 | 0.0011 | 52 |
| 0.0047 | 0.0007 | 53 |
| 0.0041 | 0.0006 | 54 |
| 0.0056 | 0.0012 | 55 |
| 0.0035 | 0.0016 | 56 |
| 0.0042 | 0.0011 | 57 |
| 0.0029 | 0.0006 | 58 |
| 0.0025 | 0.0004 | 59 |
| 0.0229 | 0.0085 | 60 |
| 0.0057 | 0.0075 | 61 |
| 0.0038 | 0.0050 | 62 |
| 0.0047 | 0.0014 | 63 |
| 0.0024 | 0.0006 | 64 |
| 0.0021 | 0.0005 | 65 |
| 0.0480 | 0.0008 | 66 |
| 0.0041 | 0.0010 | 67 |
| 0.0038 | 0.0010 | 68 |
| 0.0032 | 0.0010 | 69 |
| 0.0037 | 0.0009 | 70 |
| 0.0027 | 0.0007 | 71 |
| 0.0041 | 0.0007 | 72 |
| 0.0039 | 0.0006 | 73 |
| 0.0024 | 0.0007 | 74 |
| 0.0020 | 0.0007 | 75 |
| 0.0026 | 0.0007 | 76 |
| 0.0058 | 0.0008 | 77 |
| 0.0025 | 0.0007 | 78 |
| 0.0021 | 0.0006 | 79 |
| 0.0028 | 0.0006 | 80 |
| 0.0024 | 0.0005 | 81 |
| 0.0015 | 0.0005 | 82 |
| 0.0100 | 0.0005 | 83 |
| 0.0018 | 0.0006 | 84 |
| 0.0039 | 0.0007 | 85 |
| 0.0019 | 0.0007 | 86 |
| 0.0022 | 0.0007 | 87 |
| 0.0021 | 0.0007 | 88 |
| 0.0025 | 0.0007 | 89 |
| 0.0014 | 0.0006 | 90 |
| 0.0014 | 0.0006 | 91 |
| 0.0038 | 0.0006 | 92 |
| 0.0024 | 0.0006 | 93 |
| 0.0017 | 0.0005 | 94 |
| 0.0020 | 0.0005 | 95 |
| 0.0030 | 0.0005 | 96 |
| 0.0032 | 0.0005 | 97 |
| 0.0019 | 0.0005 | 98 |
Framework versions
- Transformers 4.46.2
- TensorFlow 2.17.0
- Datasets 3.1.0
- Tokenizers 0.20.3