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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: canine_vowelizer_0701_retrain |
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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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# canine_vowelizer_0701_retrain |
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This model is a fine-tuned version of [Buseak/canine_vowelizer_0701](https://huggingface.co/Buseak/canine_vowelizer_0701) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0066 |
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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: 0.9980 |
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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: 10 |
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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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| 0.0816 | 1.0 | 976 | 0.0322 | 1.0000 | 1.0000 | 1.0000 | 0.9891 | |
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| 0.0776 | 2.0 | 1952 | 0.0273 | 0.9999 | 1.0000 | 1.0000 | 0.9906 | |
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| 0.0694 | 3.0 | 2928 | 0.0228 | 0.9999 | 1.0000 | 1.0000 | 0.9924 | |
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| 0.0617 | 4.0 | 3904 | 0.0181 | 1.0000 | 1.0000 | 1.0000 | 0.9939 | |
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| 0.0559 | 5.0 | 4880 | 0.0144 | 1.0000 | 1.0000 | 1.0000 | 0.9952 | |
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| 0.0477 | 6.0 | 5856 | 0.0120 | 1.0000 | 1.0000 | 1.0000 | 0.9962 | |
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| 0.0438 | 7.0 | 6832 | 0.0098 | 1.0000 | 1.0000 | 1.0000 | 0.9969 | |
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| 0.0397 | 8.0 | 7808 | 0.0080 | 1.0000 | 1.0000 | 1.0000 | 0.9975 | |
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| 0.0365 | 9.0 | 8784 | 0.0071 | 1.0000 | 1.0000 | 1.0000 | 0.9978 | |
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| 0.0328 | 10.0 | 9760 | 0.0066 | 1.0000 | 1.0000 | 1.0000 | 0.9980 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.13.3 |
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