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knet-gpt-detection-project – AI Model by cacbon-dioxit | AlphaNeural AI
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knet-gpt-detection-project
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transformers
tensorboard
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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knet-gpt-detection-project
This model is a fine-tuned version of
distilbert-base-cased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0070
Accuracy: 0.9981
F1: 0.9974
Precision: 0.9966
Recall: 0.9983
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: 64
eval_batch_size: 64
seed: 42
optimizer: Use 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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.0176
1.0
1371
0.0094
0.9975
0.9967
0.9969
0.9964
0.0039
2.0
2742
0.0070
0.9981
0.9974
0.9966
0.9983
Framework versions
Transformers 4.47.1
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0
