wmduggan41
/

kd-distilBERT-clinc

Text Classification

generated_from_trainer

Inference Endpoints

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kd-distilBERT-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: 0.7849
Accuracy: 0.9165

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
4.2571	1.0	318	3.2374	0.7126
2.591	2.0	636	1.8546	0.8477
1.539	3.0	954	1.1561	0.8939
1.0142	4.0	1272	0.8673	0.91
0.806	5.0	1590	0.7849	0.9165

Framework versions

Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.7.1
Tokenizers 0.13.2

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Dataset used to train wmduggan41/kd-distilBERT-clinc

Evaluation results

Accuracy on clinc_oos
self-reported

0.916

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