bert-base – AI Model by MikeStru | AlphaNeural AI | AlphaNeural AI

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MikeStru/
bert-base

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text-classification

generated_from_trainer

google-bert/bert-base-cased

autotrain_compatible

endpoints_compatible

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bert-base

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

Loss: 0.2143
F1: 0.6772
Accuracy: 0.9520

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: 1e-05
train_batch_size: 16
eval_batch_size: 64
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy
0.0069	0.5021	120	0.1918	0.6842	0.9528
0.0053	1.0042	240	0.2304	0.6391	0.9520
0.0037	1.5063	360	0.2143	0.6772	0.9520

Framework versions

Transformers 4.46.2
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3