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

Loss: 0.1953
Accuracy: 0.931
Auc: 0.98

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Auc
0.5987	1.0	263	0.4602	0.862	0.942
0.4339	2.0	526	0.3387	0.873	0.957
0.3674	3.0	789	0.2844	0.896	0.966
0.3266	4.0	1052	0.2732	0.891	0.972
0.2931	5.0	1315	0.2235	0.92	0.975
0.287	6.0	1578	0.2233	0.92	0.977
0.2784	7.0	1841	0.2101	0.931	0.979
0.2689	8.0	2104	0.2008	0.929	0.979
0.2601	9.0	2367	0.2005	0.931	0.98
0.2558	10.0	2630	0.1953	0.931	0.98

Framework versions

Transformers 4.49.0
Pytorch 2.6.0+cu124
Datasets 3.4.1
Tokenizers 0.21.1

adrienbrdne/electra-problematic-classifier

electra-problematic-classifier

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

adrienbrdne/
electra-problematic-classifier