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bert-base-uncased-finetuned-rte-optuna-final – AI Model by minaus | AlphaNeural AI

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minaus/
bert-base-uncased-finetuned-rte-optuna-final

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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bert-base-uncased-finetuned-rte-optuna-final

This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

eval_loss: 1.3236
eval_accuracy: 0.6787
eval_runtime: 2.3173
eval_samples_per_second: 119.534
eval_steps_per_second: 7.768
epoch: 0.0321
step: 10

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: 4.289703048662781e-05
train_batch_size: 8
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: 4
mixed_precision_training: Native AMP

Framework versions

Transformers 4.50.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1