mbti-bert-nli-finetuned
This model is a fine-tuned version of sentence-transformers/bert-base-nli-mean-tokens on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5350
- F1: 0.6448
- Roc Auc: 0.7153
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: 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: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc |
|---|---|---|---|---|---|
| 0.5349 | 1.0 | 9913 | 0.5330 | 0.6484 | 0.7171 |
| 0.505 | 2.0 | 19826 | 0.5350 | 0.6448 | 0.7153 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.2