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---
license: mit
base_model: badokorach/afriqa_afroxlmr_squad_v2-luganda
tags:
- generated_from_keras_callback
model-index:
- name: badokorach/afriqa_afroxlmr_squad_v2-luganda_311223
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. -->
# badokorach/afriqa_afroxlmr_squad_v2-luganda_311223
This model is a fine-tuned version of [badokorach/afriqa_afroxlmr_squad_v2-luganda](https://huggingface.co/badokorach/afriqa_afroxlmr_squad_v2-luganda) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.6746
- Validation Loss: 0.0
- Epoch: 22
## 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': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 14760, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.02}
- training_precision: mixed_float16
### Training results
| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 3.4699 | 0.0 | 0 |
| 3.3401 | 0.0 | 1 |
| 3.1487 | 0.0 | 2 |
| 2.9589 | 0.0 | 3 |
| 2.7472 | 0.0 | 4 |
| 2.5135 | 0.0 | 5 |
| 2.3000 | 0.0 | 6 |
| 2.0904 | 0.0 | 7 |
| 1.9314 | 0.0 | 8 |
| 1.7617 | 0.0 | 9 |
| 1.6075 | 0.0 | 10 |
| 1.4573 | 0.0 | 11 |
| 1.3275 | 0.0 | 12 |
| 1.2261 | 0.0 | 13 |
| 1.1378 | 0.0 | 14 |
| 1.0358 | 0.0 | 15 |
| 0.9618 | 0.0 | 16 |
| 0.9082 | 0.0 | 17 |
| 0.8762 | 0.0 | 18 |
| 0.8012 | 0.0 | 19 |
| 0.7568 | 0.0 | 20 |
| 0.7120 | 0.0 | 21 |
| 0.6746 | 0.0 | 22 |
### Framework versions
- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.16.1
- Tokenizers 0.15.0
|