example-classifier

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

• Loss: 0.2453
• Accuracy: 0.9216
• F1: 0.9215

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: 5e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	313	0.2682	0.9116	0.9113
0.3048	2.0	626	0.2453	0.9216	0.9215

Framework versions

• Transformers 4.41.1
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.19.1