distilbert-base-uncased-finetuned-artificial

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

• eval_loss: 1.3241
• eval_accuracy: 0.7816
• eval_f1: 0.7801
• eval_runtime: 87.2407
• eval_samples_per_second: 57.313
• eval_steps_per_second: 3.588
• epoch: 1.07
• step: 8000

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Framework versions

• Transformers 4.37.1
• Pytorch 2.1.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.1