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# canine_vowelizer_0701

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: 0.0273
- Precision: 0.9999
- Recall: 1.0000
- F1: 1.0000
- Accuracy: 0.9905

## 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: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.521         | 1.0   | 1951  | 0.4233          | 0.9998    | 0.9999 | 0.9998 | 0.8544   |
| 0.3948        | 2.0   | 3902  | 0.3227          | 0.9998    | 1.0000 | 0.9999 | 0.8899   |
| 0.3353        | 3.0   | 5853  | 0.2592          | 0.9999    | 1.0000 | 0.9999 | 0.9116   |
| 0.2907        | 4.0   | 7804  | 0.2172          | 0.9999    | 0.9999 | 0.9999 | 0.9253   |
| 0.2503        | 5.0   | 9755  | 0.1823          | 0.9999    | 1.0000 | 0.9999 | 0.9363   |
| 0.2251        | 6.0   | 11706 | 0.1530          | 0.9999    | 1.0000 | 0.9999 | 0.9460   |
| 0.2001        | 7.0   | 13657 | 0.1299          | 0.9999    | 1.0000 | 0.9999 | 0.9540   |
| 0.1757        | 8.0   | 15608 | 0.1081          | 0.9999    | 1.0000 | 0.9999 | 0.9613   |
| 0.1602        | 9.0   | 17559 | 0.0936          | 0.9999    | 1.0000 | 0.9999 | 0.9665   |
| 0.1473        | 10.0  | 19510 | 0.0802          | 0.9999    | 1.0000 | 0.9999 | 0.9712   |
| 0.1319        | 11.0  | 21461 | 0.0700          | 0.9999    | 1.0000 | 1.0000 | 0.9748   |
| 0.1169        | 12.0  | 23412 | 0.0602          | 0.9999    | 1.0000 | 0.9999 | 0.9783   |
| 0.1071        | 13.0  | 25363 | 0.0518          | 0.9999    | 1.0000 | 0.9999 | 0.9815   |
| 0.0985        | 14.0  | 27314 | 0.0455          | 0.9999    | 1.0000 | 1.0000 | 0.9838   |
| 0.0918        | 15.0  | 29265 | 0.0402          | 0.9999    | 1.0000 | 1.0000 | 0.9859   |
| 0.0848        | 16.0  | 31216 | 0.0362          | 0.9999    | 1.0000 | 1.0000 | 0.9871   |
| 0.079         | 17.0  | 33167 | 0.0323          | 0.9999    | 1.0000 | 1.0000 | 0.9888   |
| 0.0728        | 18.0  | 35118 | 0.0295          | 0.9999    | 1.0000 | 1.0000 | 0.9897   |
| 0.0716        | 19.0  | 37069 | 0.0278          | 0.9999    | 1.0000 | 1.0000 | 0.9904   |
| 0.0686        | 20.0  | 39020 | 0.0273          | 0.9999    | 1.0000 | 1.0000 | 0.9905   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "canine_vowelizer_0701", "results": []}]}
transformers pytorch tensorboard canine token-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us