Buseak
/

spellcorrector_810_v12

+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: spellcorrector_810_v12
+  results: []
+---
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+# spellcorrector_810_v12
+This model is a fine-tuned version of [google/canine-s](https://huggingface.co/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