bert-finetuned-sem_eval-english

This model is a fine-tuned version of sentence-transformers/all-mpnet-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.5309
• F1: 0.6500
• Roc Auc: 0.7191
• Accuracy: 0.3001

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	Accuracy
0.5324	1.0	9913	0.5302	0.6542	0.7212	0.2941
0.5068	2.0	19826	0.5309	0.6500	0.7191	0.3001

Framework versions

• Transformers 4.38.1
• Pytorch 2.1.0+cu121
• Tokenizers 0.15.2