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---
base_model: distilbert-base-uncased
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: distilbert-fake-reviews-finetuned
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-fake-reviews-finetuned
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the [Fake Reviews Dataset](https://www.kaggle.com/datasets/thearijitdas/fake-reviews-dataset) (processed and cleaned version of [🚨 Fake Reviews Dataset](https://www.kaggle.com/datasets/mexwell/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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