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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: canine_vowelizer_0706_v2
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_0706_v2
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: 0.0003
- Precision: 1.0000
- Recall: 1.0000
- F1: 1.0000
- Accuracy: 1.0000
## 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: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.161 | 1.0 | 3902 | 0.1236 | 0.9999 | 1.0000 | 0.9999 | 0.9578 |
| 0.1197 | 2.0 | 7804 | 0.0883 | 1.0000 | 1.0000 | 1.0000 | 0.9689 |
| 0.0978 | 3.0 | 11706 | 0.0626 | 1.0000 | 1.0000 | 1.0000 | 0.9779 |
| 0.0808 | 4.0 | 15608 | 0.0454 | 1.0000 | 1.0000 | 1.0000 | 0.9838 |
| 0.0668 | 5.0 | 19510 | 0.0320 | 1.0000 | 1.0000 | 1.0000 | 0.9885 |
| 0.0524 | 6.0 | 23412 | 0.0219 | 1.0000 | 1.0000 | 1.0000 | 0.9921 |
| 0.042 | 7.0 | 27314 | 0.0150 | 1.0000 | 1.0000 | 1.0000 | 0.9946 |
| 0.0348 | 8.0 | 31216 | 0.0109 | 1.0000 | 1.0000 | 1.0000 | 0.9961 |
| 0.0286 | 9.0 | 35118 | 0.0072 | 1.0000 | 1.0000 | 1.0000 | 0.9974 |
| 0.025 | 10.0 | 39020 | 0.0049 | 1.0000 | 1.0000 | 1.0000 | 0.9983 |
| 0.0183 | 11.0 | 42922 | 0.0035 | 1.0000 | 1.0000 | 1.0000 | 0.9988 |
| 0.0157 | 12.0 | 46824 | 0.0025 | 1.0000 | 1.0000 | 1.0000 | 0.9992 |
| 0.0113 | 13.0 | 50726 | 0.0016 | 1.0000 | 1.0000 | 1.0000 | 0.9995 |
| 0.0097 | 14.0 | 54628 | 0.0012 | 1.0000 | 1.0000 | 1.0000 | 0.9996 |
| 0.0081 | 15.0 | 58530 | 0.0008 | 1.0000 | 1.0000 | 1.0000 | 0.9998 |
| 0.0071 | 16.0 | 62432 | 0.0007 | 1.0000 | 1.0000 | 1.0000 | 0.9998 |
| 0.0054 | 17.0 | 66334 | 0.0005 | 1.0000 | 1.0000 | 1.0000 | 0.9999 |
| 0.0044 | 18.0 | 70236 | 0.0004 | 1.0000 | 1.0000 | 1.0000 | 0.9999 |
| 0.0053 | 19.0 | 74138 | 0.0003 | 1.0000 | 1.0000 | 1.0000 | 1.0000 |
| 0.0039 | 20.0 | 78040 | 0.0003 | 1.0000 | 1.0000 | 1.0000 | 1.0000 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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