distilbert-base-uncased-finetuned-clinc

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: 0.8044
• Accuracy: 0.9213

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: 48
• eval_batch_size: 48
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
3.8167	1.57	500	2.4201	0.8013
1.7308	3.14	1000	1.1224	0.8984
0.929	4.72	1500	0.8044	0.9213

Framework versions

• Transformers 4.37.0
• Pytorch 2.6.0+cu124
• Datasets 2.14.5
• Tokenizers 0.15.2