banking-using-mybert-and-hf-pretrained-weight – AI Model by hcy60662 | AlphaNeural AI

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hcy60662/
banking-using-mybert-and-hf-pretrained-weight

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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banking-using-mybert-and-hf-pretrained-weight

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: 0.2975
F1: 0.9358
Accuracy: 0.9357

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: 0.0001
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy
0.6391	1.0	626	0.4850	0.8799	0.8808
0.2963	2.0	1252	0.3403	0.9152	0.9149
0.1519	3.0	1878	0.3603	0.9108	0.9140
0.0827	4.0	2504	0.3064	0.9306	0.9305
0.0215	5.0	3130	0.2975	0.9358	0.9357

Framework versions

Transformers 4.48.1
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0