fine-tuned-distilbert-base-uncased

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

• eval_loss: 0.5086
• eval_accuracy: {'accuracy': 0.815576323987539}
• eval_f1score: {'f1': 0.8154580580519637}
• eval_runtime: 23.9985
• eval_samples_per_second: 66.879
• eval_steps_per_second: 8.376
• step: 0

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
• lr_scheduler_warmup_steps: 320
• num_epochs: 2

Framework versions

• Transformers 4.40.0
• Pytorch 2.1.0
• Datasets 2.19.0
• Tokenizers 0.19.1