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README.md
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---
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: afriberta-small-hausa-5e-5
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# afriberta-small-hausa-5e-5
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This model is a fine-tuned version of [castorini/afriberta_small](https://huggingface.co/castorini/afriberta_small) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1600
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- Precision: 0.6808
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- Recall: 0.4937
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- F1: 0.5724
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- Accuracy: 0.9623
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.1523 | 1.0 | 1312 | 0.1338 | 0.6526 | 0.4261 | 0.5156 | 0.9583 |
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| 0.1162 | 2.0 | 2624 | 0.1300 | 0.6862 | 0.4603 | 0.5510 | 0.9614 |
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| 0.089 | 3.0 | 3936 | 0.1375 | 0.6953 | 0.4630 | 0.5559 | 0.9619 |
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| 0.0698 | 4.0 | 5248 | 0.1507 | 0.6860 | 0.4888 | 0.5708 | 0.9623 |
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| 0.0559 | 5.0 | 6560 | 0.1600 | 0.6808 | 0.4937 | 0.5724 | 0.9623 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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