bert-finetuned-sem_eval-english

This model is a fine-tuned version of bert-base-uncased on the sem_eval_2018_task_1 dataset. It achieves the following results on the evaluation set:

• Loss: 0.3308
• F1: 0.6645
• Roc Auc: 0.7642
• Accuracy: 0.2596

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
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.4155	1.0	855	0.3308	0.6645	0.7642	0.2596

Framework versions

• Transformers 4.17.0
• Pytorch 2.1.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.0