classify-clickbait-gpu
This model is a fine-tuned version of 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