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results_ynat – AI Model by shim-jh | AlphaNeural AI
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results_ynat
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transformers
safetensors
roberta
text-classification
generated_from_trainer
klue/roberta-base
finetune
autotrain_compatible
endpoints_compatible
us
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results_ynat
This model is a fine-tuned version of
klue/roberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 2.0016
Accuracy: 0.0793
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: 0.001
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.911
1.0
571
2.0016
0.0793
Framework versions
Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0
