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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bert-base-uncased-finetuned-fakenews
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. -->
# bert-base-uncased-finetuned-fakenews
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0656
- Accuracy: 0.9901
- F1: 0.9909
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.0505 | 1.0 | 3045 | 0.2405 | 0.9651 | 0.9685 |
| 0.0463 | 2.0 | 6090 | 0.0473 | 0.9872 | 0.9881 |
| 0.0272 | 3.0 | 9135 | 0.0607 | 0.9892 | 0.9900 |
| 0.0154 | 4.0 | 12180 | 0.0522 | 0.9892 | 0.9900 |
| 0.0047 | 5.0 | 15225 | 0.0717 | 0.9895 | 0.9903 |
| 0.0024 | 6.0 | 18270 | 0.0656 | 0.9901 | 0.9909 |
### Framework versions
- Transformers 4.22.0
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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