finetuning-fake-reviews-detector-model
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: 0.4370
- Accuracy: 0.8844
- Weighted f1: 0.8821
- Micro f1: 0.8844
- Macro f1: 0.8151
- Weighted recall: 0.8844
- Micro recall: 0.8844
- Macro recall: 0.8032
- Weighted precision: 0.8808
- Micro precision: 0.8844
- Macro precision: 0.8293
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: 5
Training results
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for filippoferrari/finetuning-fake-reviews-detector-model
Base model
distilbert/distilbert-base-uncased