bert-base-uncased-finetuned-clinc_oos – AI Model by nickapch | AlphaNeural AI

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nickapch/
bert-base-uncased-finetuned-clinc_oos

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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bert-base-uncased-finetuned-clinc_oos

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

Loss: 0.7744
Accuracy: {'accuracy': 0.932258064516129}
F1: {'f1': 0.9301680056033511}

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
4.2947	1.0	954	2.1707	{'accuracy': 0.8312903225806452}	{'f1': 0.8144079203282508}
1.7379	2.0	1908	1.0298	{'accuracy': 0.9209677419354839}	{'f1': 0.9177062984730477}
0.8752	3.0	2862	0.7744	{'accuracy': 0.932258064516129}	{'f1': 0.9301680056033511}

Framework versions

Transformers 4.34.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.14.0