distilbert-base-uncased-distilled-clinc – AI Model by MunSu | AlphaNeural AI

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MunSu/
distilbert-base-uncased-distilled-clinc

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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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: 0.0985
Accuracy: 0.9387

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	318	0.6287	0.7116
0.8898	2.0	636	0.2668	0.8510
0.8898	3.0	954	0.1559	0.9113
0.2678	4.0	1272	0.1246	0.9261
0.1446	5.0	1590	0.1124	0.9332
0.1446	6.0	1908	0.1059	0.9358
0.1178	7.0	2226	0.1025	0.9348
0.1071	8.0	2544	0.1007	0.9365
0.1071	9.0	2862	0.0988	0.9377
0.1021	10.0	3180	0.0985	0.9387

Framework versions

Transformers 4.26.1
Pytorch 1.8.1+cu111
Datasets 2.10.1
Tokenizers 0.11.0