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---
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: []
---

<!-- 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_3_100_Full

This model is a fine-tuned version of [Labira/LabiraPJOK_2_100_Full](https://huggingface.co/Labira/LabiraPJOK_2_100_Full) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0072
- Validation Loss: 0.0012
- Epoch: 26

## 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    |


### Framework versions

- Transformers 4.46.2
- TensorFlow 2.17.0
- Datasets 3.1.0
- Tokenizers 0.20.3