mbti-bert-nli-finetuned_v2
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: 0.5429
- F1: 0.5231
- Roc Auc: 0.6546
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: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
F1 |
Roc Auc |
| 0.5413 |
1.0 |
5948 |
0.5385 |
0.5721 |
0.6766 |
| 0.5046 |
2.0 |
11896 |
0.5429 |
0.5231 |
0.6546 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.2
