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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: spellcorrector_810_v12
    results: []

spellcorrector_810_v12

This model is a fine-tuned version of google/canine-s on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0041
  • Precision: 0.9992
  • Recall: 0.9990
  • F1: 0.9991
  • Accuracy: 0.9990

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 25

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.1941 1.0 1951 0.1593 0.9157 0.9720 0.9431 0.9616
0.1594 2.0 3902 0.1279 0.9313 0.9746 0.9524 0.9672
0.1334 3.0 5853 0.1078 0.9423 0.9772 0.9594 0.9713
0.1216 4.0 7804 0.0901 0.9537 0.9770 0.9652 0.9752
0.1061 5.0 9755 0.0745 0.9600 0.9804 0.9701 0.9789
0.092 6.0 11706 0.0600 0.9703 0.9826 0.9764 0.9830
0.0809 7.0 13657 0.0492 0.9755 0.9866 0.9810 0.9862
0.0671 8.0 15608 0.0449 0.9827 0.9837 0.9832 0.9874
0.062 9.0 17559 0.0365 0.9848 0.9878 0.9863 0.9896
0.0534 10.0 19510 0.0325 0.9873 0.9885 0.9879 0.9907
0.0474 11.0 21461 0.0267 0.9887 0.9918 0.9902 0.9922
0.042 12.0 23412 0.0228 0.9904 0.9932 0.9918 0.9933
0.0384 13.0 25363 0.0216 0.9929 0.9925 0.9927 0.9937
0.0338 14.0 27314 0.0201 0.9939 0.9935 0.9937 0.9943
0.0298 15.0 29265 0.0150 0.9949 0.9954 0.9951 0.9956
0.0262 16.0 31216 0.0128 0.9959 0.9961 0.9960 0.9962
0.0232 17.0 33167 0.0109 0.9970 0.9966 0.9968 0.9968
0.0222 18.0 35118 0.0090 0.9976 0.9977 0.9976 0.9974
0.0193 19.0 37069 0.0079 0.9979 0.9980 0.9980 0.9978
0.0185 20.0 39020 0.0068 0.9984 0.9982 0.9983 0.9981
0.016 21.0 40971 0.0057 0.9988 0.9985 0.9986 0.9985
0.0145 22.0 42922 0.0053 0.9989 0.9985 0.9987 0.9985
0.0136 23.0 44873 0.0045 0.9991 0.9988 0.9990 0.9988
0.0136 24.0 46824 0.0043 0.9992 0.9990 0.9991 0.9989
0.0116 25.0 48775 0.0041 0.9992 0.9990 0.9991 0.9990

Framework versions

  • Transformers 4.28.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3