transformers tensorboard safetensors canine token-classification generated_from_trainer base_model:Buseak/spellcorrector_17_02_050_qwerty license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: Buseak/spellcorrector_17_02_050_qwerty
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: spellcorrector_18_02_050_qwerty_v6
  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_18_02_050_qwerty_v6

This model is a fine-tuned version of [Buseak/spellcorrector_17_02_050_qwerty](https://huggingface.co/Buseak/spellcorrector_17_02_050_qwerty) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0028
- Precision: 0.9968
- Recall: 0.9941
- F1: 0.9954
- Accuracy: 0.9993

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0887        | 1.0   | 967   | 0.0551          | 0.9876    | 0.9801 | 0.9838 | 0.9842   |
| 0.0684        | 2.0   | 1934  | 0.0415          | 0.9930    | 0.9844 | 0.9887 | 0.9881   |
| 0.0581        | 3.0   | 2901  | 0.0343          | 0.9924    | 0.9855 | 0.9890 | 0.9899   |
| 0.0487        | 4.0   | 3868  | 0.0280          | 0.9925    | 0.9882 | 0.9903 | 0.9917   |
| 0.0425        | 5.0   | 4835  | 0.0241          | 0.9930    | 0.9882 | 0.9906 | 0.9930   |
| 0.0382        | 6.0   | 5802  | 0.0209          | 0.9946    | 0.9882 | 0.9914 | 0.9940   |
| 0.0333        | 7.0   | 6769  | 0.0168          | 0.9951    | 0.9909 | 0.9930 | 0.9950   |
| 0.0294        | 8.0   | 7736  | 0.0148          | 0.9941    | 0.9909 | 0.9925 | 0.9957   |
| 0.0265        | 9.0   | 8703  | 0.0121          | 0.9946    | 0.9909 | 0.9927 | 0.9964   |
| 0.0238        | 10.0  | 9670  | 0.0103          | 0.9952    | 0.9919 | 0.9935 | 0.9970   |
| 0.0216        | 11.0  | 10637 | 0.0090          | 0.9978    | 0.9930 | 0.9954 | 0.9974   |
| 0.0193        | 12.0  | 11604 | 0.0076          | 0.9952    | 0.9930 | 0.9941 | 0.9979   |
| 0.0175        | 13.0  | 12571 | 0.0065          | 0.9973    | 0.9936 | 0.9954 | 0.9982   |
| 0.016         | 14.0  | 13538 | 0.0055          | 0.9973    | 0.9936 | 0.9954 | 0.9985   |
| 0.0137        | 15.0  | 14505 | 0.0045          | 0.9968    | 0.9936 | 0.9952 | 0.9988   |
| 0.0127        | 16.0  | 15472 | 0.0039          | 0.9973    | 0.9941 | 0.9957 | 0.9990   |
| 0.0118        | 17.0  | 16439 | 0.0034          | 0.9978    | 0.9941 | 0.9960 | 0.9991   |
| 0.0111        | 18.0  | 17406 | 0.0030          | 0.9968    | 0.9941 | 0.9954 | 0.9992   |
| 0.0104        | 19.0  | 18373 | 0.0029          | 0.9968    | 0.9941 | 0.9954 | 0.9993   |
| 0.0099        | 20.0  | 19340 | 0.0028          | 0.9968    | 0.9941 | 0.9954 | 0.9993   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
