alperk3003
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End of training
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README.md
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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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config: full
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split: test
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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: 0.9763541841355022
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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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# language-detection-fine-tuned-on-xlm-roberta-base
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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: 0.1635
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- Accuracy: 0.9764
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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: 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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 0.2855 | 1.0 | 22194 | 0.1635 | 0.9764 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.0
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- Tokenizers 0.13.2
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runs/Feb28_13-37-39_a33b359fd696/events.out.tfevents.1677591535.a33b359fd696.1103.0
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runs/Feb28_13-37-39_a33b359fd696/events.out.tfevents.1677595669.a33b359fd696.1103.2
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