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license: mit
base_model: Davlan/afro-xlmr-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: only_english
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. -->
# only_english
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: 0.1647
- Precision: 0.6988
- Recall: 0.5376
- F1: 0.6077
- Accuracy: 0.9561
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1733 | 1.0 | 1312 | 0.1466 | 0.684 | 0.4374 | 0.5336 | 0.9514 |
| 0.1394 | 2.0 | 2624 | 0.1439 | 0.7089 | 0.4819 | 0.5737 | 0.9546 |
| 0.1123 | 3.0 | 3936 | 0.1417 | 0.6983 | 0.5299 | 0.6026 | 0.9556 |
| 0.0899 | 4.0 | 5248 | 0.1522 | 0.7075 | 0.5303 | 0.6062 | 0.9563 |
| 0.0744 | 5.0 | 6560 | 0.1647 | 0.6988 | 0.5376 | 0.6077 | 0.9561 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3
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