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vowelizer_1203_v8

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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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+
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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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+
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+ # vowelizer_1203_v8
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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