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results – AI Model by Ghazi-nak | AlphaNeural AI
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Ghazi-nak
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results
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transformers
tensorboard
safetensors
roberta
text-classification
generated_from_trainer
FacebookAI/roberta-base
finetune
autotrain_compatible
endpoints_compatible
us
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This model is a fine-tuned version of
roberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.7984
Accuracy: 0.705
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: 5e-05
train_batch_size: 8
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 200
num_epochs: 1
Training results
Framework versions
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1
