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OR_finetuned_classification – AI Model by pingkeest | AlphaNeural AI
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OR_finetuned_classification
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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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OR_finetuned_classification
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: 0.6007
F1: 0.6667
Roc Auc: 0.8095
Accuracy: 0.6667
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: 0.0002
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: 300
Training results
Training Loss
Epoch
Step
Validation Loss
F1
Roc Auc
Accuracy
0.0016
79.0
790
0.4859
0.6667
0.8095
0.6667
0.0006
158.0
1580
0.5649
0.6667
0.8095
0.6667
0.0004
237.0
2370
0.6007
0.6667
0.8095
0.6667
Framework versions
Transformers 4.45.2
Pytorch 2.4.0+cu124
Datasets 3.0.1
Tokenizers 0.20.1
