toxigen-albert-binary-clsf
This model is a fine-tuned version of albert/albert-base-v1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- Precision: 1.0000
- Recall: 1.0000
- Accuracy: 1.0000
Model description
More information needed
Intended uses & limitations
Finetuning albert/albert-base-v1 on the toxigen/toxigen-data dataset on the task of binary classfication.
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy |
|---|---|---|---|---|---|---|
| 0.0 | 1.0 | 3137 | 0.0000 | 1.0000 | 1.0000 | 1.0000 |
| 0.0001 | 2.0 | 6274 | 0.0000 | 1.0000 | 1.0000 | 1.0000 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1