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--- |
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license: apache-2.0 |
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base_model: ntu-spml/distilhubert |
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tags: |
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- generated_from_trainer |
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datasets: |
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- audiofolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: distilhubert-finetuned-accents |
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results: |
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- task: |
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name: Audio Classification |
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type: audio-classification |
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dataset: |
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name: audiofolder |
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type: audiofolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.2708333333333333 |
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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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# distilhubert-finetuned-accents |
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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0374 |
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- Accuracy: 0.2708 |
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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: 5e-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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- lr_scheduler_warmup_ratio: 0.6 |
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- num_epochs: 14 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 2.4741 | 1.0 | 48 | 2.4767 | 0.1042 | |
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| 2.4794 | 2.0 | 96 | 2.4594 | 0.1042 | |
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| 2.4795 | 3.0 | 144 | 2.4242 | 0.1042 | |
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| 2.3636 | 4.0 | 192 | 2.3929 | 0.1042 | |
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| 2.2958 | 5.0 | 240 | 2.3036 | 0.1667 | |
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| 2.2177 | 6.0 | 288 | 2.1868 | 0.1771 | |
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| 1.9929 | 7.0 | 336 | 2.0746 | 0.2396 | |
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| 1.9842 | 8.0 | 384 | 2.0638 | 0.2292 | |
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| 1.934 | 9.0 | 432 | 2.0566 | 0.2292 | |
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| 1.7302 | 10.0 | 480 | 2.1105 | 0.2083 | |
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| 1.6971 | 11.0 | 528 | 1.9927 | 0.2292 | |
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| 1.4807 | 12.0 | 576 | 2.0434 | 0.2396 | |
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| 1.3496 | 13.0 | 624 | 2.0579 | 0.2708 | |
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| 1.3694 | 14.0 | 672 | 2.0374 | 0.2708 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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