distilbert-base-uncased-distilled-clinc

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

• Loss: 0.1580
• Accuracy: 0.9487

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: 13

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.7033	1.0	318	1.2016	0.7610
0.9281	2.0	636	0.6128	0.8855
0.4901	3.0	954	0.3447	0.9252
0.289	4.0	1272	0.2389	0.9403
0.2016	5.0	1590	0.2000	0.9455
0.1647	6.0	1908	0.1826	0.9484
0.1446	7.0	2226	0.1723	0.9487
0.1329	8.0	2544	0.1672	0.9477
0.1255	9.0	2862	0.1639	0.9494
0.1211	10.0	3180	0.1621	0.9497
0.1171	11.0	3498	0.1591	0.95
0.1149	12.0	3816	0.1585	0.9494
0.1136	13.0	4134	0.1580	0.9487

Framework versions

• Transformers 4.16.2
• Pytorch 2.4.1+cu121
• Datasets 1.16.1
• Tokenizers 0.19.1