---
license: apache-2.0
base_model: albert/albert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: classify-clickbait-gpu
  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. -->

# classify-clickbait-gpu

This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co/albert/albert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0130
- Accuracy: 0.9976
- F1: 0.9976
- Precision: 0.9976
- Recall: 0.9976
- Accuracy Label Clickbait: 0.9933
- Accuracy Label Factual: 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Accuracy Label Clickbait | Accuracy Label Factual |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------------------------:|:----------------------:|
| 0.0546        | 0.4831 | 100  | 0.0504          | 0.9902   | 0.9902 | 0.9902    | 0.9902 | 0.9866                   | 0.9923                 |
| 0.0071        | 0.9662 | 200  | 0.0060          | 0.9988   | 0.9988 | 0.9988    | 0.9988 | 0.9967                   | 1.0                    |
| 0.0008        | 1.4493 | 300  | 0.0088          | 0.9976   | 0.9976 | 0.9976    | 0.9976 | 0.9933                   | 1.0                    |
| 0.0006        | 1.9324 | 400  | 0.0310          | 0.9939   | 0.9939 | 0.9939    | 0.9939 | 0.9833                   | 1.0                    |
| 0.0007        | 2.4155 | 500  | 0.0002          | 1.0      | 1.0    | 1.0       | 1.0    | 1.0                      | 1.0                    |
| 0.0009        | 2.8986 | 600  | 0.0079          | 0.9988   | 0.9988 | 0.9988    | 0.9988 | 0.9967                   | 1.0                    |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1