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Update README.md
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README.md
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## Training procedure
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### Framework versions
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## Training procedure
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Fine-tuning was done via the `Trainer` API. Here is the [Jupyter notebook](https://github.com/DominguesM/language-detection/blob/main/Language_Detector_Lora.ipynb) with the training code.
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 64
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- eval_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- num_epochs: 2
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### Training results
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The validation results on the `valid` split of the Language Identification dataset are summarised here below.
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 1.4403 | 1.0 | 1094 | 0.0591 | 0.9952 | 0.9952 |
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| 0.0256 | 2.0 | 2188 | 0.0272 | 0.9955 | 0.9955 |
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In short, it achieves the following results on the validation set:
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- Loss: 0.0298
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- Accuracy: 0.9946
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- F1: 0.9946
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### Framework versions
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