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bert-finetuned-sem_eval-english – AI Model by AndriiDemk | AlphaNeural AI
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AndriiDemk
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bert-finetuned-sem_eval-english
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transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-finetuned-sem_eval-english
This model is a fine-tuned version of
bert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0716
F1: 0.9706
Roc Auc: 0.9799
Accuracy: 0.965
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: 8
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
F1
Roc Auc
Accuracy
0.0818
1.0
1000
0.0716
0.9706
0.9799
0.965
Framework versions
Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0
