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si_bert_intent

Text Classification
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bert
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si_bert_intent / README.md
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bert finetuned model for intent detection
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metadata
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: bert_intent
    results: []

bert_intent

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

  • Loss: 0.0169
  • Accuracy: 0.9982

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: 1e-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: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.2615 1.0 692 0.0516 0.9809
0.0191 2.0 1384 0.0231 0.9947
0.0083 3.0 2076 0.0140 0.9982
0.0051 4.0 2768 0.0101 0.9975
0.0028 5.0 3460 0.0075 0.9979
0.0013 6.0 4152 0.0064 0.9979
0.0008 7.0 4844 0.0073 0.9979
0.0004 8.0 5536 0.0069 0.9979
0.0003 9.0 6228 0.0072 0.9979
0.0002 10.0 6920 0.0075 0.9979
0.0002 11.0 7612 0.0077 0.9979
0.0001 12.0 8304 0.0080 0.9979
0.0001 13.0 8996 0.0083 0.9979
0.0001 14.0 9688 0.0087 0.9979
0.0 15.0 10380 0.0093 0.9979
0.0 16.0 11072 0.0097 0.9982
0.0 17.0 11764 0.0096 0.9979
0.0 18.0 12456 0.0106 0.9979
0.0 19.0 13148 0.0108 0.9979
0.0 20.0 13840 0.0110 0.9979
0.0 21.0 14532 0.0111 0.9979
0.0 22.0 15224 0.0116 0.9979
0.0 23.0 15916 0.0116 0.9979
0.0 24.0 16608 0.0125 0.9982
0.0 25.0 17300 0.0130 0.9982
0.0 26.0 17992 0.0124 0.9979
0.0 27.0 18684 0.0129 0.9979
0.0 28.0 19376 0.0138 0.9982
0.0 29.0 20068 0.0140 0.9982
0.0 30.0 20760 0.0145 0.9982
0.0 31.0 21452 0.0144 0.9982
0.0 32.0 22144 0.0146 0.9982
0.0 33.0 22836 0.0152 0.9982
0.0 34.0 23528 0.0151 0.9982
0.0 35.0 24220 0.0151 0.9982
0.0 36.0 24912 0.0153 0.9982
0.0 37.0 25604 0.0155 0.9982
0.0 38.0 26296 0.0158 0.9982
0.0 39.0 26988 0.0159 0.9982
0.0 40.0 27680 0.0163 0.9982
0.0 41.0 28372 0.0168 0.9982
0.0 42.0 29064 0.0167 0.9982
0.0 43.0 29756 0.0167 0.9982
0.0 44.0 30448 0.0168 0.9982
0.0 45.0 31140 0.0168 0.9982
0.0 46.0 31832 0.0168 0.9982
0.0 47.0 32524 0.0168 0.9982
0.0 48.0 33216 0.0168 0.9982
0.0 49.0 33908 0.0169 0.9982
0.0 50.0 34600 0.0169 0.9982

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.1
  • Datasets 2.19.2
  • Tokenizers 0.19.1