distilbert-fake-reviews-finetuned
This model is a fine-tuned version of distilbert-base-uncased on the Fake Reviews Dataset (processed and cleaned version of 🚨 Fake Reviews Dataset), containing 20k fake reviews and 20k real product reviews. OR = Original reviews (presumably human created and authentic); CG = Computer-generated fake reviews.
It achieves the following results on the evaluation set:
- Loss: 0.1241
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.172 | 1.0 | 2022 | 0.0987 |
| 0.003 | 2.0 | 4044 | 0.1477 |
| 0.0002 | 3.0 | 6066 | 0.1241 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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Model tree for theArijitDas/distilbert-finetuned-fake-reviews
Base model
distilbert/distilbert-base-uncased