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End of training

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: xlm-roberta-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: AmharicNewsCharacterNormalized
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+ results: []
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+ ---
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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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+
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+ # AmharicNewsCharacterNormalized
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+
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+ This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2054
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+ - Accuracy: 0.9538
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+ - Precision: 0.9539
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+ - Recall: 0.9538
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+ - F1: 0.9538
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 32
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+ - eval_batch_size: 32
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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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+ - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.2737 | 1.0 | 945 | 0.1984 | 0.9175 | 0.9197 | 0.9175 | 0.9172 |
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+ | 0.2651 | 2.0 | 1890 | 0.2313 | 0.9409 | 0.9408 | 0.9409 | 0.9407 |
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+ | 0.2155 | 3.0 | 2835 | 0.1687 | 0.9480 | 0.9480 | 0.9480 | 0.9479 |
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+ | 0.4065 | 4.0 | 3780 | 0.2072 | 0.9439 | 0.9483 | 0.9439 | 0.9443 |
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+ | 0.0785 | 5.0 | 4725 | 0.2054 | 0.9538 | 0.9539 | 0.9538 | 0.9538 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.1
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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