bert-base-uncased-finetuned-swag – AI Model by tahalachab | AlphaNeural AI

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tahalachab/
bert-base-uncased-finetuned-swag

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bert-base-uncased-finetuned-swag

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: 1.0064
Accuracy: 0.7922

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: 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

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7606	1.0	4597	0.6083	0.7643
0.3823	2.0	9194	0.5873	0.7867
0.1325	3.0	13791	1.0064	0.7922

Framework versions

Transformers 4.48.3
Pytorch 2.5.1+cu124
Datasets 3.3.1
Tokenizers 0.21.0