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distilbert-base-uncased-finetuned-fake-news-fg – AI Model by xraypub | AlphaNeural AI
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xraypub
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distilbert-base-uncased-finetuned-fake-news-fg
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transformers
tensorboard
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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distilbert-base-uncased-finetuned-fake-news-fg
This model is a fine-tuned version of
distilbert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.6691
Precision: 1.0
Recall: 1.0
Acc: 1.0
F1: 1.0
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: 4
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
Acc
F1
0.7018
1.0
2
0.6867
0.25
0.5
0.5
0.3333
0.6845
2.0
4
0.6792
0.25
0.5
0.5
0.3333
0.6644
3.0
6
0.6726
0.25
0.5
0.5
0.3333
0.6579
4.0
8
0.6694
1.0
1.0
1.0
1.0
Framework versions
Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.1
