---
library_name: transformers
license: mit
base_model: Labira/LabiraPJOK_3x_50
tags:
- generated_from_keras_callback
model-index:
- name: Labira/LabiraPJOK_5x_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_5x_50

This model is a fine-tuned version of [Labira/LabiraPJOK_3x_50](https://huggingface.co/Labira/LabiraPJOK_3x_50) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0274
- Validation Loss: 3.1328
- Epoch: 44

## 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': 150, '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 |
|:----------:|:---------------:|:-----:|
| 3.2696     | 2.9298          | 0     |
| 1.9565     | 2.6626          | 1     |
| 1.6690     | 2.7837          | 2     |
| 1.1679     | 2.9196          | 3     |
| 1.0975     | 2.8046          | 4     |
| 0.8930     | 2.6822          | 5     |
| 0.6527     | 2.6118          | 6     |
| 0.5637     | 2.5444          | 7     |
| 0.4854     | 2.5175          | 8     |
| 0.4389     | 2.5464          | 9     |
| 0.3206     | 2.5893          | 10    |
| 0.3225     | 2.6538          | 11    |
| 0.1880     | 2.7504          | 12    |
| 0.1288     | 2.8371          | 13    |
| 0.1381     | 2.9128          | 14    |
| 0.0994     | 2.9468          | 15    |
| 0.1544     | 2.9312          | 16    |
| 0.0978     | 2.9279          | 17    |
| 0.0492     | 2.9426          | 18    |
| 0.0612     | 2.9733          | 19    |
| 0.1016     | 3.0228          | 20    |
| 0.0554     | 3.0772          | 21    |
| 0.0768     | 3.1331          | 22    |
| 0.0277     | 3.1720          | 23    |
| 0.0403     | 3.1906          | 24    |
| 0.0730     | 3.1962          | 25    |
| 0.0204     | 3.1958          | 26    |
| 0.0731     | 3.1981          | 27    |
| 0.0414     | 3.1874          | 28    |
| 0.0316     | 3.1657          | 29    |
| 0.0324     | 3.1507          | 30    |
| 0.0526     | 3.1275          | 31    |
| 0.0369     | 3.1141          | 32    |
| 0.0406     | 3.1091          | 33    |
| 0.0214     | 3.1127          | 34    |
| 0.0209     | 3.1207          | 35    |
| 0.0139     | 3.1172          | 36    |
| 0.0215     | 3.1166          | 37    |
| 0.0140     | 3.1168          | 38    |
| 0.0277     | 3.1187          | 39    |
| 0.0131     | 3.1214          | 40    |
| 0.0184     | 3.1226          | 41    |
| 0.0286     | 3.1256          | 42    |
| 0.0144     | 3.1297          | 43    |
| 0.0274     | 3.1328          | 44    |


### Framework versions

- Transformers 4.44.2
- TensorFlow 2.17.0
- Datasets 3.0.1
- Tokenizers 0.19.1