---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-clickbait-task1-20-epoch-post_title
  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-base-uncased-clickbait-task1-20-epoch-post_title

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co./distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4236
- Accuracy: 0.67

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 200  | 0.8500          | 0.6425   |
| No log        | 2.0   | 400  | 0.7542          | 0.6975   |
| 0.7863        | 3.0   | 600  | 0.8059          | 0.695    |
| 0.7863        | 4.0   | 800  | 0.9656          | 0.6875   |
| 0.3245        | 5.0   | 1000 | 1.1785          | 0.655    |
| 0.3245        | 6.0   | 1200 | 1.4214          | 0.675    |
| 0.3245        | 7.0   | 1400 | 1.7879          | 0.655    |
| 0.0784        | 8.0   | 1600 | 1.9526          | 0.66     |
| 0.0784        | 9.0   | 1800 | 2.0289          | 0.6575   |
| 0.0233        | 10.0  | 2000 | 2.1091          | 0.675    |
| 0.0233        | 11.0  | 2200 | 2.1530          | 0.67     |
| 0.0233        | 12.0  | 2400 | 2.2120          | 0.67     |
| 0.0091        | 13.0  | 2600 | 2.2703          | 0.6875   |
| 0.0091        | 14.0  | 2800 | 2.3026          | 0.68     |
| 0.0064        | 15.0  | 3000 | 2.3154          | 0.685    |
| 0.0064        | 16.0  | 3200 | 2.3335          | 0.6825   |
| 0.0064        | 17.0  | 3400 | 2.3667          | 0.6825   |
| 0.0036        | 18.0  | 3600 | 2.3959          | 0.6775   |
| 0.0036        | 19.0  | 3800 | 2.4513          | 0.6625   |
| 0.0043        | 20.0  | 4000 | 2.4236          | 0.67     |


### Framework versions

- Transformers 4.44.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1