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---
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
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