|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: distilroberta-clickbait |
|
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. --> |
|
|
|
# distilroberta-clickbait |
|
|
|
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on a dataset of headlines. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0268 |
|
- Acc: 0.9963 |
|
|
|
## Training and evaluation data |
|
|
|
The following data sources were used: |
|
* 32k headlines classified as clickbait/not-clickbait from [kaggle](https://www.kaggle.com/amananandrai/clickbait-dataset) |
|
* A dataset of headlines from https://github.com/MotiBaadror/Clickbait-Detection |
|
|
|
## Training procedure |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 2e-05 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 32 |
|
- seed: 12345 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 16 |
|
- num_epochs: 20 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Acc | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 0.0195 | 1.0 | 981 | 0.0192 | 0.9954 | |
|
| 0.0026 | 2.0 | 1962 | 0.0172 | 0.9963 | |
|
| 0.0031 | 3.0 | 2943 | 0.0275 | 0.9945 | |
|
| 0.0003 | 4.0 | 3924 | 0.0268 | 0.9963 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.11.3 |
|
- Pytorch 1.10.1 |
|
- Datasets 1.17.0 |
|
- Tokenizers 0.10.3 |
|
|
