Altruism_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: 0.7202
- Accuracy: 0.6986
- Precision: 0.6613
- Recall: 0.8130
- F1: 0.7293
- Auc: 0.7806
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 | 0.6034 | 0.6650 | 0.61 | 0.9127 | 0.7313 | 0.7688 |
| No log | 2.0 | 236 | 0.5704 | 0.7173 | 0.6843 | 0.8055 | 0.7400 | 0.7867 |
| No log | 3.0 | 354 | 0.5799 | 0.7073 | 0.6566 | 0.8678 | 0.7476 | 0.7832 |
| No log | 4.0 | 472 | 0.6729 | 0.6725 | 0.6194 | 0.8928 | 0.7314 | 0.7767 |
| 0.5183 | 5.0 | 590 | 0.7202 | 0.6986 | 0.6613 | 0.8130 | 0.7293 | 0.7806 |
Framework versions
- Transformers 4.44.1
- Pytorch 1.11.0
- Datasets 2.12.0
- Tokenizers 0.19.1