fakenews_binaryclassifier_distilbert_cased
This model is a fine-tuned version of distilbert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6203
- Accuracy: 0.736
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: 3e-06
- 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6867 | 1.0 | 63 | 0.6704 | 0.648 |
| 0.6618 | 2.0 | 126 | 0.6406 | 0.684 |
| 0.6335 | 3.0 | 189 | 0.6203 | 0.736 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for vishalk4u/fakenews_binaryclassifier_distilbert_cased
Base model
distilbert/distilbert-base-cased