finetuned-bert-mrpc – AI Model by MasterShomya | AlphaNeural AI

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MasterShomya/
finetuned-bert-mrpc

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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finetuned-bert-mrpc

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

Loss: 0.4725
Accuracy: 0.8382
F1: 0.8881

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: 32
eval_batch_size: 32
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

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.5236	0.4348	50	0.4882	0.7647	0.8452
0.4277	0.8696	100	0.3845	0.8431	0.8940
0.2727	1.3043	150	0.3824	0.8529	0.8980
0.2285	1.7391	200	0.3646	0.8358	0.8831
0.1305	2.1739	250	0.3605	0.8652	0.9002
0.1193	2.6087	300	0.4725	0.8382	0.8881

Framework versions

Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.2