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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: vowelizer_1203_v8 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# vowelizer_1203_v8 |
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This model is a fine-tuned version of [Buseak/vowelizer_1203_v6](https://huggingface.co/Buseak/vowelizer_1203_v6) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0001 |
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- Precision: 1.0000 |
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- Recall: 1.0000 |
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- F1: 1.0000 |
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- Accuracy: 1.0000 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.0731 | 1.0 | 967 | 0.0292 | 0.9860 | 0.9750 | 0.9805 | 0.9908 | |
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| 0.0462 | 2.0 | 1934 | 0.0171 | 0.9916 | 0.9850 | 0.9883 | 0.9945 | |
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| 0.0327 | 3.0 | 2901 | 0.0104 | 0.9950 | 0.9907 | 0.9929 | 0.9967 | |
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| 0.0243 | 4.0 | 3868 | 0.0063 | 0.9968 | 0.9953 | 0.9960 | 0.9981 | |
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| 0.0197 | 5.0 | 4835 | 0.0042 | 0.9979 | 0.9968 | 0.9973 | 0.9987 | |
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| 0.0159 | 6.0 | 5802 | 0.0031 | 0.9981 | 0.9979 | 0.9980 | 0.9991 | |
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| 0.0132 | 7.0 | 6769 | 0.0018 | 0.9990 | 0.9985 | 0.9988 | 0.9995 | |
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| 0.0115 | 8.0 | 7736 | 0.0014 | 0.9991 | 0.9991 | 0.9991 | 0.9996 | |
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| 0.0097 | 9.0 | 8703 | 0.0010 | 0.9994 | 0.9994 | 0.9994 | 0.9997 | |
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| 0.0082 | 10.0 | 9670 | 0.0007 | 0.9996 | 0.9995 | 0.9996 | 0.9998 | |
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| 0.0066 | 11.0 | 10637 | 0.0005 | 0.9998 | 0.9997 | 0.9998 | 0.9999 | |
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| 0.006 | 12.0 | 11604 | 0.0004 | 0.9998 | 0.9998 | 0.9998 | 0.9999 | |
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| 0.0055 | 13.0 | 12571 | 0.0003 | 0.9997 | 0.9997 | 0.9997 | 0.9999 | |
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| 0.0047 | 14.0 | 13538 | 0.0002 | 0.9999 | 0.9999 | 0.9999 | 1.0000 | |
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| 0.004 | 15.0 | 14505 | 0.0002 | 0.9999 | 0.9999 | 0.9999 | 1.0000 | |
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| 0.0034 | 16.0 | 15472 | 0.0001 | 0.9999 | 0.9999 | 0.9999 | 1.0000 | |
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| 0.0032 | 17.0 | 16439 | 0.0001 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | |
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| 0.003 | 18.0 | 17406 | 0.0001 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | |
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| 0.0027 | 19.0 | 18373 | 0.0001 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | |
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| 0.0024 | 20.0 | 19340 | 0.0001 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.13.3 |
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