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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: vowelizer_1203_v10
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. -->
# vowelizer_1203_v10
This model is a fine-tuned version of [Buseak/vowelizer_1203_v9](https://huggingface.co/Buseak/vowelizer_1203_v9) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- 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: 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0383 | 1.0 | 967 | 0.0127 | 0.9939 | 0.9893 | 0.9916 | 0.9961 |
| 0.0237 | 2.0 | 1934 | 0.0064 | 0.9967 | 0.9950 | 0.9959 | 0.9980 |
| 0.016 | 3.0 | 2901 | 0.0039 | 0.9978 | 0.9966 | 0.9972 | 0.9987 |
| 0.0119 | 4.0 | 3868 | 0.0024 | 0.9987 | 0.9982 | 0.9985 | 0.9993 |
| 0.0097 | 5.0 | 4835 | 0.0016 | 0.9990 | 0.9989 | 0.9990 | 0.9995 |
| 0.0078 | 6.0 | 5802 | 0.0012 | 0.9992 | 0.9993 | 0.9992 | 0.9996 |
| 0.0064 | 7.0 | 6769 | 0.0007 | 0.9996 | 0.9995 | 0.9996 | 0.9998 |
| 0.0056 | 8.0 | 7736 | 0.0007 | 0.9997 | 0.9996 | 0.9996 | 0.9998 |
| 0.005 | 9.0 | 8703 | 0.0004 | 0.9998 | 0.9997 | 0.9997 | 0.9999 |
| 0.0042 | 10.0 | 9670 | 0.0004 | 0.9997 | 0.9997 | 0.9997 | 0.9999 |
| 0.0037 | 11.0 | 10637 | 0.0002 | 0.9999 | 0.9998 | 0.9999 | 0.9999 |
| 0.0031 | 12.0 | 11604 | 0.0002 | 0.9999 | 0.9999 | 0.9999 | 1.0000 |
| 0.0026 | 13.0 | 12571 | 0.0001 | 0.9999 | 1.0000 | 0.9999 | 1.0000 |
| 0.0024 | 14.0 | 13538 | 0.0001 | 0.9999 | 0.9999 | 0.9999 | 1.0000 |
| 0.002 | 15.0 | 14505 | 0.0001 | 1.0000 | 1.0000 | 1.0000 | 1.0000 |
| 0.0019 | 16.0 | 15472 | 0.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 |
| 0.0017 | 17.0 | 16439 | 0.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 |
| 0.0014 | 18.0 | 17406 | 0.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 |
| 0.0011 | 19.0 | 18373 | 0.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 |
| 0.0012 | 20.0 | 19340 | 0.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.13.3
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