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: 0.3313
• Accuracy: 0.9419

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: 0.00016475242401724032
• 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: cosine
• num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	318	0.3697	0.9132
1.0928	2.0	636	0.3539	0.9226
1.0928	3.0	954	0.3790	0.9281
0.1164	4.0	1272	0.3579	0.9345
0.0587	5.0	1590	0.3705	0.9281
0.0587	6.0	1908	0.3543	0.9410
0.0344	7.0	2226	0.3665	0.9348
0.0244	8.0	2544	0.3510	0.9358
0.0244	9.0	2862	0.3344	0.9423
0.0153	10.0	3180	0.3335	0.9403
0.0153	11.0	3498	0.3302	0.9426
0.0126	12.0	3816	0.3305	0.9423
0.0103	13.0	4134	0.3301	0.9423
0.0103	14.0	4452	0.3311	0.9416
0.0095	15.0	4770	0.3313	0.9419

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 2.4.0
• Tokenizers 0.19.1