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Intent-classification-12kv2

Text Classification
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Safetensors
bert
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Intent-classification-12kv2 / README.md
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metadata
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: Intent-classification-12kv2
    results: []

Intent-classification-12kv2

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: 0.0074
  • Accuracy: 0.9984
  • F1: 0.9983
  • Precision: 0.9983
  • Recall: 0.9983

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
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 10
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
1.742 0.05 10 1.4822 0.6954 0.6918 0.7288 0.6966
1.2849 0.11 20 0.9533 0.8713 0.8699 0.8899 0.8729
0.8226 0.16 30 0.5235 0.9786 0.9786 0.9790 0.9785
0.399 0.21 40 0.2295 0.9812 0.9812 0.9811 0.9817
0.1871 0.26 50 0.1168 0.9839 0.9839 0.9844 0.9836
0.0855 0.32 60 0.0508 0.9928 0.9928 0.9928 0.9928
0.0546 0.37 70 0.0300 0.9947 0.9947 0.9948 0.9947
0.0226 0.42 80 0.0271 0.9947 0.9948 0.9947 0.9948
0.0306 0.47 90 0.0416 0.9888 0.9887 0.9894 0.9883
0.0336 0.53 100 0.0157 0.9970 0.9970 0.9970 0.9971
0.0373 0.58 110 0.0214 0.9951 0.9951 0.9952 0.9951
0.0094 0.63 120 0.0121 0.9970 0.9971 0.9971 0.9970
0.0077 0.68 130 0.0094 0.9980 0.9980 0.9980 0.9981
0.0253 0.74 140 0.0077 0.9987 0.9987 0.9987 0.9987
0.0233 0.79 150 0.0075 0.9987 0.9987 0.9987 0.9987
0.0068 0.84 160 0.0080 0.9987 0.9987 0.9987 0.9987
0.0286 0.89 170 0.0141 0.9964 0.9964 0.9964 0.9964
0.0139 0.95 180 0.0104 0.9970 0.9970 0.9970 0.9971
0.0043 1.0 190 0.0074 0.9977 0.9977 0.9977 0.9976
0.0122 1.05 200 0.0065 0.9987 0.9987 0.9987 0.9987
0.0071 1.11 210 0.0059 0.9980 0.9980 0.9981 0.9980
0.0025 1.16 220 0.0083 0.9984 0.9984 0.9984 0.9983
0.0232 1.21 230 0.0057 0.9984 0.9984 0.9984 0.9984
0.0035 1.26 240 0.0056 0.9987 0.9987 0.9987 0.9987
0.0246 1.32 250 0.0053 0.9984 0.9984 0.9984 0.9983
0.0023 1.37 260 0.0063 0.9980 0.9980 0.9981 0.9980
0.0021 1.42 270 0.0048 0.9984 0.9984 0.9984 0.9983
0.002 1.47 280 0.0028 0.9997 0.9997 0.9997 0.9997
0.022 1.53 290 0.0023 0.9997 0.9997 0.9997 0.9997
0.0135 1.58 300 0.0046 0.9987 0.9987 0.9987 0.9987
0.0026 1.63 310 0.0082 0.9977 0.9977 0.9979 0.9976
0.0019 1.68 320 0.0043 0.9990 0.9990 0.9991 0.9990
0.0017 1.74 330 0.0035 0.9993 0.9994 0.9994 0.9994
0.0019 1.79 340 0.0015 1.0 1.0 1.0 1.0
0.0014 1.84 350 0.0013 1.0 1.0 1.0 1.0
0.0014 1.89 360 0.0013 1.0 1.0 1.0 1.0
0.0013 1.95 370 0.0012 1.0 1.0 1.0 1.0
0.0013 2.0 380 0.0011 1.0 1.0 1.0 1.0
0.0012 2.05 390 0.0011 1.0 1.0 1.0 1.0
0.0011 2.11 400 0.0011 1.0 1.0 1.0 1.0
0.0011 2.16 410 0.0010 1.0 1.0 1.0 1.0
0.0011 2.21 420 0.0010 1.0 1.0 1.0 1.0
0.0014 2.26 430 0.0009 1.0 1.0 1.0 1.0
0.001 2.32 440 0.0009 1.0 1.0 1.0 1.0
0.001 2.37 450 0.0009 1.0 1.0 1.0 1.0
0.0009 2.42 460 0.0009 1.0 1.0 1.0 1.0
0.0009 2.47 470 0.0008 1.0 1.0 1.0 1.0
0.0009 2.53 480 0.0008 1.0 1.0 1.0 1.0
0.0009 2.58 490 0.0008 1.0 1.0 1.0 1.0
0.0009 2.63 500 0.0008 1.0 1.0 1.0 1.0
0.0008 2.68 510 0.0008 1.0 1.0 1.0 1.0
0.0008 2.74 520 0.0008 1.0 1.0 1.0 1.0
0.0008 2.79 530 0.0007 1.0 1.0 1.0 1.0
0.0008 2.84 540 0.0007 1.0 1.0 1.0 1.0
0.0008 2.89 550 0.0007 1.0 1.0 1.0 1.0
0.0008 2.95 560 0.0007 1.0 1.0 1.0 1.0
0.0007 3.0 570 0.0007 1.0 1.0 1.0 1.0
0.0009 3.05 580 0.0007 1.0 1.0 1.0 1.0
0.0007 3.11 590 0.0006 1.0 1.0 1.0 1.0
0.0007 3.16 600 0.0006 1.0 1.0 1.0 1.0
0.0007 3.21 610 0.0006 1.0 1.0 1.0 1.0
0.0007 3.26 620 0.0006 1.0 1.0 1.0 1.0
0.0007 3.32 630 0.0006 1.0 1.0 1.0 1.0
0.0007 3.37 640 0.0006 1.0 1.0 1.0 1.0
0.0006 3.42 650 0.0006 1.0 1.0 1.0 1.0
0.0006 3.47 660 0.0006 1.0 1.0 1.0 1.0
0.0006 3.53 670 0.0006 1.0 1.0 1.0 1.0
0.0006 3.58 680 0.0006 1.0 1.0 1.0 1.0
0.0006 3.63 690 0.0006 1.0 1.0 1.0 1.0
0.0006 3.68 700 0.0006 1.0 1.0 1.0 1.0
0.0006 3.74 710 0.0006 1.0 1.0 1.0 1.0
0.0006 3.79 720 0.0006 1.0 1.0 1.0 1.0
0.0006 3.84 730 0.0006 1.0 1.0 1.0 1.0
0.0006 3.89 740 0.0005 1.0 1.0 1.0 1.0
0.0006 3.95 750 0.0005 1.0 1.0 1.0 1.0
0.0006 4.0 760 0.0005 1.0 1.0 1.0 1.0
0.0006 4.05 770 0.0005 1.0 1.0 1.0 1.0
0.0006 4.11 780 0.0005 1.0 1.0 1.0 1.0
0.0006 4.16 790 0.0005 1.0 1.0 1.0 1.0
0.0006 4.21 800 0.0005 1.0 1.0 1.0 1.0
0.0006 4.26 810 0.0005 1.0 1.0 1.0 1.0
0.0006 4.32 820 0.0005 1.0 1.0 1.0 1.0
0.0006 4.37 830 0.0005 1.0 1.0 1.0 1.0
0.0006 4.42 840 0.0005 1.0 1.0 1.0 1.0
0.0006 4.47 850 0.0005 1.0 1.0 1.0 1.0
0.0006 4.53 860 0.0005 1.0 1.0 1.0 1.0
0.0006 4.58 870 0.0005 1.0 1.0 1.0 1.0
0.0005 4.63 880 0.0005 1.0 1.0 1.0 1.0
0.0006 4.68 890 0.0005 1.0 1.0 1.0 1.0
0.0005 4.74 900 0.0005 1.0 1.0 1.0 1.0
0.0005 4.79 910 0.0005 1.0 1.0 1.0 1.0
0.0006 4.84 920 0.0005 1.0 1.0 1.0 1.0
0.0005 4.89 930 0.0005 1.0 1.0 1.0 1.0
0.0006 4.95 940 0.0005 1.0 1.0 1.0 1.0
0.0005 5.0 950 0.0005 1.0 1.0 1.0 1.0

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.2
  • Datasets 2.1.0
  • Tokenizers 0.15.2