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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_2105_v6 |
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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_2105_v6 |
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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: 0.1704 |
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- Precision: 0.9998 |
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- Recall: 0.9998 |
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- F1: 0.9998 |
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- Accuracy: 0.9391 |
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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: 15 |
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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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| 0.4826 | 1.0 | 3885 | 0.4310 | 0.9997 | 0.9998 | 0.9997 | 0.8467 | |
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| 0.4118 | 2.0 | 7770 | 0.3556 | 0.9997 | 0.9998 | 0.9997 | 0.8748 | |
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| 0.369 | 3.0 | 11655 | 0.3126 | 0.9997 | 0.9998 | 0.9997 | 0.8893 | |
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| 0.339 | 4.0 | 15540 | 0.2811 | 0.9997 | 0.9998 | 0.9998 | 0.9014 | |
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| 0.3192 | 5.0 | 19425 | 0.2589 | 0.9997 | 0.9998 | 0.9998 | 0.9095 | |
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| 0.3052 | 6.0 | 23310 | 0.2399 | 0.9997 | 0.9998 | 0.9998 | 0.9157 | |
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| 0.281 | 7.0 | 27195 | 0.2252 | 0.9997 | 0.9998 | 0.9998 | 0.9207 | |
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| 0.2749 | 8.0 | 31080 | 0.2117 | 0.9998 | 0.9998 | 0.9998 | 0.9248 | |
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| 0.2589 | 9.0 | 34965 | 0.2011 | 0.9998 | 0.9998 | 0.9998 | 0.9285 | |
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| 0.253 | 10.0 | 38850 | 0.1940 | 0.9998 | 0.9998 | 0.9998 | 0.9314 | |
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| 0.2428 | 11.0 | 42735 | 0.1842 | 0.9998 | 0.9998 | 0.9998 | 0.9348 | |
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| 0.2433 | 12.0 | 46620 | 0.1783 | 0.9998 | 0.9998 | 0.9998 | 0.9365 | |
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| 0.2265 | 13.0 | 50505 | 0.1751 | 0.9998 | 0.9998 | 0.9998 | 0.9375 | |
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| 0.2244 | 14.0 | 54390 | 0.1721 | 0.9998 | 0.9998 | 0.9998 | 0.9387 | |
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| 0.2203 | 15.0 | 58275 | 0.1704 | 0.9998 | 0.9998 | 0.9998 | 0.9391 | |
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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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