results2

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

• Loss: 0.1753
• Accuracy: 0.9265

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

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2492	1.0	1000	0.2094	0.9205
0.1423	2.0	2000	0.1753	0.9265

Framework versions

• Transformers 4.45.2
• Pytorch 2.4.1
• Datasets 3.0.1
• Tokenizers 0.20.1