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bert_finetuning_test – AI Model by SiSi1126 | AlphaNeural AI

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SiSi1126/
bert_finetuning_test

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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trainer_output

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

Loss: 0.7168
Accuracy: 0.8505
F1: 0.8968
Combined Score: 0.8736

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: 8
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: 3.0

Training results

Framework versions

Transformers 4.51.0.dev0
Pytorch 2.6.0+cpu
Datasets 3.4.1
Tokenizers 0.21.1