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---
library_name: transformers
license: mit
base_model: Labira/LabiraPJOK_2x_50
tags:
- generated_from_keras_callback
model-index:
- name: Labira/LabiraPJOK_3x_50
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# Labira/LabiraPJOK_3x_50
This model is a fine-tuned version of [Labira/LabiraPJOK_2x_50](https://huggingface.co/Labira/LabiraPJOK_2x_50) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0125
- Validation Loss: 1.5431
- 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: {'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': 450, '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 |
|:----------:|:---------------:|:-----:|
| 2.7214 | 1.2242 | 0 |
| 1.5828 | 1.1158 | 1 |
| 0.9946 | 1.0677 | 2 |
| 0.7404 | 1.2115 | 3 |
| 0.5481 | 1.0920 | 4 |
| 0.3599 | 1.1031 | 5 |
| 0.2659 | 1.1035 | 6 |
| 0.2725 | 1.1251 | 7 |
| 0.2207 | 1.1364 | 8 |
| 0.1379 | 1.2039 | 9 |
| 0.1687 | 1.2331 | 10 |
| 0.1154 | 1.1677 | 11 |
| 0.1126 | 1.2093 | 12 |
| 0.0953 | 1.2532 | 13 |
| 0.0753 | 1.2455 | 14 |
| 0.0519 | 1.2544 | 15 |
| 0.0603 | 1.2511 | 16 |
| 0.0609 | 1.2736 | 17 |
| 0.0530 | 1.2692 | 18 |
| 0.0384 | 1.2869 | 19 |
| 0.0337 | 1.3048 | 20 |
| 0.0304 | 1.3314 | 21 |
| 0.0565 | 1.3378 | 22 |
| 0.0351 | 1.3842 | 23 |
| 0.0480 | 1.4148 | 24 |
| 0.0308 | 1.3959 | 25 |
| 0.0454 | 1.3768 | 26 |
| 0.0557 | 1.4469 | 27 |
| 0.0397 | 1.4431 | 28 |
| 0.0212 | 1.4441 | 29 |
| 0.0251 | 1.4262 | 30 |
| 0.0291 | 1.4412 | 31 |
| 0.0194 | 1.5155 | 32 |
| 0.0238 | 1.5136 | 33 |
| 0.0209 | 1.5002 | 34 |
| 0.0183 | 1.4976 | 35 |
| 0.0204 | 1.5533 | 36 |
| 0.0183 | 1.6057 | 37 |
| 0.0147 | 1.6047 | 38 |
| 0.0137 | 1.6029 | 39 |
| 0.0090 | 1.5879 | 40 |
| 0.0323 | 1.5802 | 41 |
| 0.0181 | 1.5748 | 42 |
| 0.0144 | 1.5629 | 43 |
| 0.0215 | 1.5534 | 44 |
| 0.0058 | 1.5442 | 45 |
| 0.0144 | 1.5485 | 46 |
| 0.0122 | 1.5449 | 47 |
| 0.0139 | 1.5428 | 48 |
| 0.0125 | 1.5431 | 49 |
### Framework versions
- Transformers 4.44.2
- TensorFlow 2.17.0
- Datasets 3.0.1
- Tokenizers 0.19.1
|