nli-mpnet-base-v2_mbti_full
This model is a fine-tuned version of sentence-transformers/nli-mpnet-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5768
- F1: 0.4807
- Roc Auc: 0.6200
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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc |
|---|---|---|---|---|---|
| No log | 1.0 | 325 | 0.5771 | 0.4804 | 0.6197 |
| 0.5798 | 2.0 | 651 | 0.5766 | 0.0 | 0.5 |
| 0.5798 | 3.0 | 976 | 0.5764 | 0.0 | 0.5 |
| 0.576 | 4.0 | 1302 | 0.5760 | 0.0 | 0.5 |
| 0.5762 | 5.0 | 1627 | 0.5762 | 0.0 | 0.5 |
| 0.5762 | 6.0 | 1953 | 0.5760 | 0.0 | 0.5 |
| 0.5762 | 7.0 | 2278 | 0.5761 | 0.4804 | 0.6197 |
| 0.5741 | 8.0 | 2604 | 0.5759 | 0.4804 | 0.6197 |
| 0.5741 | 9.0 | 2929 | 0.5759 | 0.4804 | 0.6197 |
| 0.5769 | 9.98 | 3250 | 0.5760 | 0.4804 | 0.6197 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2