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results – AI Model by fredenck | AlphaNeural AI
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This model is a fine-tuned version of
on the None dataset. It achieves the following results on the evaluation set:
Loss: 8.2985
Accuracy: 0.2497
F1: 0.3970
Precision: 0.3318
Recall: 0.494
Roc Auc: 0.2799
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: 1e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
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
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1
