narcissism_binary
This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9656
- Accuracy: 0.7034
- Precision: 0.8052
- Recall: 0.5375
- F1: 0.6447
- Auc: 0.7577
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: 32
- eval_batch_size: 32
- seed: 1234
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Auc |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 117 | 0.6010 | 0.6621 | 0.8916 | 0.37 | 0.5230 | 0.7373 |
| No log | 2.0 | 234 | 0.5663 | 0.6984 | 0.7870 | 0.545 | 0.6440 | 0.7643 |
| No log | 3.0 | 351 | 0.6275 | 0.7096 | 0.7979 | 0.5625 | 0.6598 | 0.7694 |
| No log | 4.0 | 468 | 0.8468 | 0.6984 | 0.8565 | 0.4775 | 0.6132 | 0.7551 |
| 0.4623 | 5.0 | 585 | 0.9656 | 0.7034 | 0.8052 | 0.5375 | 0.6447 | 0.7577 |
Framework versions
- Transformers 4.44.1
- Pytorch 1.11.0
- Datasets 2.12.0
- Tokenizers 0.19.1