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L1-classifier-Transliteration – AI Model by Zlovoblachko | AlphaNeural AI
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L1-classifier-Transliteration
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transformers
tensorboard
safetensors
xlm-roberta
text-classification
generated_from_trainer
FacebookAI/xlm-roberta-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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L1-classifier-Transliteration
This model is a fine-tuned version of
FacebookAI/xlm-roberta-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1161
F1: 0.9648
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
F1
No log
1.0
182
0.1055
0.9620
No log
2.0
364
0.1161
0.9648
Framework versions
Transformers 4.40.1
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1
