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results_flausch_classification_gbert-large_span_classifier – AI Model by Wiebke | AlphaNeural AI
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Wiebke
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results_flausch_classification_gbert-large_span_classifier
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transformers
safetensors
bert
text-classification
generated_from_trainer
deepset/gbert-large
finetune
mit
autotrain_compatible
endpoints_compatible
us
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results_flausch_classification_gbert-large_span_classifier
This model is a fine-tuned version of
deepset/gbert-large
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3241
Accuracy: 0.9305
F1: 0.9287
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: 2e-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
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.5824
0.6588
500
0.3772
0.8941
0.8920
0.3311
1.3175
1000
0.3267
0.9137
0.9124
0.2542
1.9763
1500
0.2943
0.9249
0.9231
0.1611
2.6350
2000
0.3241
0.9305
0.9287
Framework versions
Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.1
