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DSChallenge_Roberta – AI Model by leonardosaveri | AlphaNeural AI
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leonardosaveri
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DSChallenge_Roberta
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transformers
pytorch
tensorboard
xlm-roberta
text-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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DSChallenge_Roberta
This model is a fine-tuned version of
xlm-roberta-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2321
Accuracy: 0.9333
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
Accuracy
0.3884
1.0
746
0.1892
0.9303
0.227
2.0
1492
0.2321
0.9333
Framework versions
Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3
