Assertiveness_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: 0.8562
- Accuracy: 0.6077
- Precision: 0.6075
- Recall: 0.6060
- F1: 0.6067
- Auc: 0.6514
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 | 118 | 0.6655 | 0.5928 | 0.6108 | 0.5087 | 0.5551 | 0.6526 |
| No log | 2.0 | 236 | 0.6989 | 0.5716 | 0.5403 | 0.9526 | 0.6895 | 0.6611 |
| No log | 3.0 | 354 | 0.6783 | 0.6139 | 0.6022 | 0.6683 | 0.6336 | 0.6583 |
| No log | 4.0 | 472 | 0.8562 | 0.6077 | 0.6075 | 0.6060 | 0.6067 | 0.6514 |
Framework versions
- Transformers 4.44.1
- Pytorch 1.11.0
- Datasets 2.12.0
- Tokenizers 0.19.1