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vowelizer_1203_v9

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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_v9
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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_v9
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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: 0.0000
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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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+ | 0.0516 | 1.0 | 967 | 0.0195 | 0.9907 | 0.9827 | 0.9867 | 0.9941 |
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+ | 0.0318 | 2.0 | 1934 | 0.0109 | 0.9950 | 0.9901 | 0.9925 | 0.9967 |
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+ | 0.0225 | 3.0 | 2901 | 0.0065 | 0.9960 | 0.9950 | 0.9955 | 0.9980 |
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+ | 0.017 | 4.0 | 3868 | 0.0037 | 0.9981 | 0.9968 | 0.9975 | 0.9988 |
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+ | 0.013 | 5.0 | 4835 | 0.0026 | 0.9986 | 0.9980 | 0.9983 | 0.9992 |
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+ | 0.0103 | 6.0 | 5802 | 0.0018 | 0.9989 | 0.9988 | 0.9989 | 0.9995 |
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+ | 0.0091 | 7.0 | 6769 | 0.0012 | 0.9992 | 0.9990 | 0.9991 | 0.9996 |
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+ | 0.0073 | 8.0 | 7736 | 0.0009 | 0.9994 | 0.9992 | 0.9993 | 0.9997 |
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+ | 0.0065 | 9.0 | 8703 | 0.0006 | 0.9996 | 0.9996 | 0.9996 | 0.9998 |
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+ | 0.0057 | 10.0 | 9670 | 0.0004 | 0.9997 | 0.9997 | 0.9997 | 0.9999 |
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+ | 0.0045 | 11.0 | 10637 | 0.0003 | 0.9997 | 0.9997 | 0.9997 | 0.9999 |
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+ | 0.004 | 12.0 | 11604 | 0.0003 | 0.9999 | 0.9998 | 0.9998 | 0.9999 |
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+ | 0.0035 | 13.0 | 12571 | 0.0002 | 0.9998 | 0.9998 | 0.9998 | 0.9999 |
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+ | 0.003 | 14.0 | 13538 | 0.0002 | 0.9999 | 0.9999 | 0.9999 | 1.0000 |
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+ | 0.0029 | 15.0 | 14505 | 0.0001 | 0.9999 | 0.9999 | 0.9999 | 1.0000 |
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+ | 0.0024 | 16.0 | 15472 | 0.0001 | 1.0000 | 0.9999 | 0.9999 | 1.0000 |
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+ | 0.0021 | 17.0 | 16439 | 0.0001 | 0.9999 | 0.9999 | 0.9999 | 1.0000 |
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+ | 0.0019 | 18.0 | 17406 | 0.0001 | 1.0000 | 1.0000 | 1.0000 | 1.0000 |
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+ | 0.0018 | 19.0 | 18373 | 0.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 |
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+ | 0.0015 | 20.0 | 19340 | 0.0000 | 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