---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: canine_vowelizer_2105_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. -->

# canine_vowelizer_2105_v6

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: 0.1704
- Precision: 0.9998
- Recall: 0.9998
- F1: 0.9998
- Accuracy: 0.9391

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4826        | 1.0   | 3885  | 0.4310          | 0.9997    | 0.9998 | 0.9997 | 0.8467   |
| 0.4118        | 2.0   | 7770  | 0.3556          | 0.9997    | 0.9998 | 0.9997 | 0.8748   |
| 0.369         | 3.0   | 11655 | 0.3126          | 0.9997    | 0.9998 | 0.9997 | 0.8893   |
| 0.339         | 4.0   | 15540 | 0.2811          | 0.9997    | 0.9998 | 0.9998 | 0.9014   |
| 0.3192        | 5.0   | 19425 | 0.2589          | 0.9997    | 0.9998 | 0.9998 | 0.9095   |
| 0.3052        | 6.0   | 23310 | 0.2399          | 0.9997    | 0.9998 | 0.9998 | 0.9157   |
| 0.281         | 7.0   | 27195 | 0.2252          | 0.9997    | 0.9998 | 0.9998 | 0.9207   |
| 0.2749        | 8.0   | 31080 | 0.2117          | 0.9998    | 0.9998 | 0.9998 | 0.9248   |
| 0.2589        | 9.0   | 34965 | 0.2011          | 0.9998    | 0.9998 | 0.9998 | 0.9285   |
| 0.253         | 10.0  | 38850 | 0.1940          | 0.9998    | 0.9998 | 0.9998 | 0.9314   |
| 0.2428        | 11.0  | 42735 | 0.1842          | 0.9998    | 0.9998 | 0.9998 | 0.9348   |
| 0.2433        | 12.0  | 46620 | 0.1783          | 0.9998    | 0.9998 | 0.9998 | 0.9365   |
| 0.2265        | 13.0  | 50505 | 0.1751          | 0.9998    | 0.9998 | 0.9998 | 0.9375   |
| 0.2244        | 14.0  | 54390 | 0.1721          | 0.9998    | 0.9998 | 0.9998 | 0.9387   |
| 0.2203        | 15.0  | 58275 | 0.1704          | 0.9998    | 0.9998 | 0.9998 | 0.9391   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3