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bert-base-multilingual-uncased-fine-tuned-hs-new – AI Model by PaceKW | AlphaNeural AI
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PaceKW
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bert-base-multilingual-uncased-fine-tuned-hs-new
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transformers
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-multilingual-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-base-multilingual-uncased-fine-tuned-hs-new
This model is a fine-tuned version of
google-bert/bert-base-multilingual-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.6934
F1: 0.5955
Roc Auc: 0.4985
Accuracy: 0.0
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: 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
F1
Roc Auc
Accuracy
0.6939
1.0
2002
0.6937
0.5629
0.4993
0.0
0.6939
2.0
4004
0.6934
0.5955
0.4985
0.0
0.6938
3.0
6006
0.6936
0.5643
0.4973
0.0005
0.6936
4.0
8008
0.6933
0.5842
0.5002
0.0010
Framework versions
Transformers 4.51.3
Pytorch 2.7.0+cu128
Datasets 3.6.0
Tokenizers 0.21.1
