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language-detection-fine-tuned-on-xlm-roberta-base – AI Model by ivanlau | AlphaNeural AI
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ivanlau
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language-detection-fine-tuned-on-xlm-roberta-base
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transformers
pytorch
tensorboard
xlm-roberta
text-classification
generated_from_trainer
common_language
mit
model-index
autotrain_compatible
endpoints_compatible
us
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language-detection-fine-tuned-on-xlm-roberta-base
This model is a fine-tuned version of
xlm-roberta-base
on the
common_language
dataset. It achieves the following results on the evaluation set:
Loss: 0.1886
Accuracy: 0.9738
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 3e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.1
1.0
22194
0.1886
0.9738
Framework versions
Transformers 4.12.5
Pytorch 1.10.0+cu111
Datasets 1.15.1
Tokenizers 0.10.3
Notebook
notebook
