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