gokuls/bert-uncased-massive-intent-classification

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bert-uncased-massive-intent-classification

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

• —Loss: 0.8396
• —Accuracy: 0.8854

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: 5e-05
• —trainbatchsize: 16
• —evalbatchsize: 16
• —seed: 33
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 15
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.22.1
• —Pytorch 1.12.1+cu113
• —Datasets 2.4.0
• —Tokenizers 0.12.1