metadata
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Fake-News-Detector
results: []
Fake-News-Detector
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- Accuracy: 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: 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: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0 | 0.09 | 100 | 0.0000 | 1.0 |
| 0.0 | 0.19 | 200 | 0.0000 | 1.0 |
| 0.0 | 0.28 | 300 | 0.0000 | 1.0 |
| 0.0 | 0.37 | 400 | 0.0000 | 1.0 |
| 0.0 | 0.47 | 500 | 0.0000 | 1.0 |
| 0.0 | 0.56 | 600 | 0.0000 | 1.0 |
| 0.0 | 0.65 | 700 | 0.0000 | 1.0 |
| 0.0 | 0.75 | 800 | 0.0000 | 1.0 |
| 0.0 | 0.84 | 900 | 0.0000 | 1.0 |
| 0.0 | 0.93 | 1000 | 0.0000 | 1.0 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.1