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---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: afro-xlmr-base-hausa-seed-30
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# afro-xlmr-base-hausa-seed-30
This model is a fine-tuned version of [Davlan/afro-xlmr-base](https://huggingface.co/Davlan/afro-xlmr-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1635
- Precision: 0.7407
- Recall: 0.5630
- F1: 0.6398
- Accuracy: 0.9599
## 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:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1599 | 1.0 | 1312 | 0.1431 | 0.7178 | 0.4516 | 0.5544 | 0.9536 |
| 0.1198 | 2.0 | 2624 | 0.1364 | 0.7155 | 0.5470 | 0.6200 | 0.9581 |
| 0.0932 | 3.0 | 3936 | 0.1381 | 0.7165 | 0.5708 | 0.6354 | 0.9588 |
| 0.0705 | 4.0 | 5248 | 0.1564 | 0.7529 | 0.5461 | 0.6330 | 0.9600 |
| 0.0559 | 5.0 | 6560 | 0.1635 | 0.7407 | 0.5630 | 0.6398 | 0.9599 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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