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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_0706_v2 |
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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_0706_v2 |
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This model is a fine-tuned version of [google/canine-s](https://huggingface.co/google/canine-s) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0003 |
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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: 2 |
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- eval_batch_size: 2 |
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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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| 0.161 | 1.0 | 3902 | 0.1236 | 0.9999 | 1.0000 | 0.9999 | 0.9578 | |
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| 0.1197 | 2.0 | 7804 | 0.0883 | 1.0000 | 1.0000 | 1.0000 | 0.9689 | |
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| 0.0978 | 3.0 | 11706 | 0.0626 | 1.0000 | 1.0000 | 1.0000 | 0.9779 | |
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| 0.0808 | 4.0 | 15608 | 0.0454 | 1.0000 | 1.0000 | 1.0000 | 0.9838 | |
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| 0.0668 | 5.0 | 19510 | 0.0320 | 1.0000 | 1.0000 | 1.0000 | 0.9885 | |
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| 0.0524 | 6.0 | 23412 | 0.0219 | 1.0000 | 1.0000 | 1.0000 | 0.9921 | |
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| 0.042 | 7.0 | 27314 | 0.0150 | 1.0000 | 1.0000 | 1.0000 | 0.9946 | |
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| 0.0348 | 8.0 | 31216 | 0.0109 | 1.0000 | 1.0000 | 1.0000 | 0.9961 | |
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| 0.0286 | 9.0 | 35118 | 0.0072 | 1.0000 | 1.0000 | 1.0000 | 0.9974 | |
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| 0.025 | 10.0 | 39020 | 0.0049 | 1.0000 | 1.0000 | 1.0000 | 0.9983 | |
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| 0.0183 | 11.0 | 42922 | 0.0035 | 1.0000 | 1.0000 | 1.0000 | 0.9988 | |
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| 0.0157 | 12.0 | 46824 | 0.0025 | 1.0000 | 1.0000 | 1.0000 | 0.9992 | |
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| 0.0113 | 13.0 | 50726 | 0.0016 | 1.0000 | 1.0000 | 1.0000 | 0.9995 | |
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| 0.0097 | 14.0 | 54628 | 0.0012 | 1.0000 | 1.0000 | 1.0000 | 0.9996 | |
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| 0.0081 | 15.0 | 58530 | 0.0008 | 1.0000 | 1.0000 | 1.0000 | 0.9998 | |
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| 0.0071 | 16.0 | 62432 | 0.0007 | 1.0000 | 1.0000 | 1.0000 | 0.9998 | |
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| 0.0054 | 17.0 | 66334 | 0.0005 | 1.0000 | 1.0000 | 1.0000 | 0.9999 | |
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| 0.0044 | 18.0 | 70236 | 0.0004 | 1.0000 | 1.0000 | 1.0000 | 0.9999 | |
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| 0.0053 | 19.0 | 74138 | 0.0003 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | |
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| 0.0039 | 20.0 | 78040 | 0.0003 | 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 2.0.1+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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