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rotten – AI Model by MiVaCod | AlphaNeural AI
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MiVaCod
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rotten
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transformers
safetensors
bert
text-classification
classification
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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rotten
This model is a fine-tuned version of
bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.8598
Accuracy: 0.8527
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.405
1.0
1067
0.3657
0.8546
0.225
2.0
2134
0.7075
0.8433
0.0711
3.0
3201
0.8598
0.8527
Framework versions
Transformers 4.40.2
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1
