Buseak
/

spellcorrector_710_v8

+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: spellcorrector_710_v8
+  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_710_v8
+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: 0.0144
+- Precision: 0.9961
+- Recall: 0.9962
+- F1: 0.9962
+- Accuracy: 0.9957
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.2237        | 1.0   | 1951  | 0.1844          | 0.9061    | 0.9700 | 0.9370 | 0.9557   |
+| 0.1882        | 2.0   | 3902  | 0.1577          | 0.9144    | 0.9719 | 0.9423 | 0.9598   |
+| 0.1669        | 3.0   | 5853  | 0.1389          | 0.9311    | 0.9689 | 0.9497 | 0.9633   |
+| 0.154         | 4.0   | 7804  | 0.1234          | 0.9343    | 0.9751 | 0.9543 | 0.9669   |
+| 0.141         | 5.0   | 9755  | 0.1076          | 0.9480    | 0.9734 | 0.9605 | 0.9711   |
+| 0.1286        | 6.0   | 11706 | 0.0959          | 0.9584    | 0.9746 | 0.9664 | 0.9747   |
+| 0.1131        | 7.0   | 13657 | 0.0799          | 0.9624    | 0.9792 | 0.9708 | 0.9780   |
+| 0.1016        | 8.0   | 15608 | 0.0714          | 0.9696    | 0.9801 | 0.9748 | 0.9805   |
+| 0.0915        | 9.0   | 17559 | 0.0627          | 0.9737    | 0.9821 | 0.9779 | 0.9825   |
+| 0.0839        | 10.0  | 19510 | 0.0574          | 0.9781    | 0.9830 | 0.9806 | 0.9839   |
+| 0.0761        | 11.0  | 21461 | 0.0500          | 0.9808    | 0.9849 | 0.9828 | 0.9858   |
+| 0.069         | 12.0  | 23412 | 0.0437          | 0.9807    | 0.9887 | 0.9847 | 0.9873   |
+| 0.0644        | 13.0  | 25363 | 0.0404          | 0.9849    | 0.9882 | 0.9866 | 0.9882   |
+| 0.057         | 14.0  | 27314 | 0.0371          | 0.9871    | 0.9892 | 0.9881 | 0.9892   |
+| 0.0555        | 15.0  | 29265 | 0.0343          | 0.9890    | 0.9895 | 0.9893 | 0.9900   |
+| 0.0512        | 16.0  | 31216 | 0.0288          | 0.9899    | 0.9919 | 0.9909 | 0.9914   |
+| 0.0464        | 17.0  | 33167 | 0.0265          | 0.9914    | 0.9922 | 0.9918 | 0.9920   |
+| 0.0424        | 18.0  | 35118 | 0.0234          | 0.9924    | 0.9937 | 0.9931 | 0.9929   |
+| 0.0391        | 19.0  | 37069 | 0.0215          | 0.9940    | 0.9936 | 0.9938 | 0.9936   |
+| 0.0375        | 20.0  | 39020 | 0.0195          | 0.9944    | 0.9944 | 0.9944 | 0.9942   |
+| 0.0344        | 21.0  | 40971 | 0.0178          | 0.9952    | 0.9949 | 0.9950 | 0.9947   |
+| 0.032         | 22.0  | 42922 | 0.0160          | 0.9955    | 0.9957 | 0.9956 | 0.9952   |
+| 0.0299        | 23.0  | 44873 | 0.0153          | 0.9957    | 0.9960 | 0.9958 | 0.9954   |
+| 0.0291        | 24.0  | 46824 | 0.0145          | 0.9961    | 0.9961 | 0.9961 | 0.9957   |
+| 0.0289        | 25.0  | 48775 | 0.0144          | 0.9961    | 0.9962 | 0.9962 | 0.9957   |
+### Framework versions
+- Transformers 4.28.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3