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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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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - common_language
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: language-detection-fine-tuned-on-xlm-roberta-base
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: common_language
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+ type: common_language
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+ args: full
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9738386718094919
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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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+ # language-detection-fine-tuned-on-xlm-roberta-base
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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 common_language dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1886
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+ - Accuracy: 0.9738
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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: 3e-05
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+ - train_batch_size: 1
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+ - eval_batch_size: 1
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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: 1
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+ - mixed_precision_training: Native AMP
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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 |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.1 | 1.0 | 22194 | 0.1886 | 0.9738 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.12.5
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+ - Pytorch 1.10.0+cu111
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+ - Datasets 1.15.1
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+ - Tokenizers 0.10.3
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