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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: 0.39097744360902253 |
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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: 1.8429 |
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- Accuracy: 0.3910 |
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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: 0.7 |
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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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| 2.5546 | 1.0 | 67 | 2.5463 | 0.1729 | |
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| 2.4756 | 2.0 | 134 | 2.4641 | 0.1654 | |
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| 2.3726 | 3.0 | 201 | 2.4065 | 0.2030 | |
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| 2.464 | 4.0 | 268 | 2.3753 | 0.2256 | |
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| 2.2215 | 5.0 | 335 | 2.3161 | 0.2481 | |
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| 2.346 | 6.0 | 402 | 2.2739 | 0.2556 | |
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| 1.8318 | 7.0 | 469 | 2.0260 | 0.3383 | |
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| 1.9612 | 8.0 | 536 | 1.8926 | 0.3684 | |
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| 1.7699 | 9.0 | 603 | 1.8646 | 0.3835 | |
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| 1.5864 | 10.0 | 670 | 2.0469 | 0.3083 | |
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| 1.5774 | 11.0 | 737 | 1.8156 | 0.3609 | |
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| 1.5087 | 12.0 | 804 | 1.8061 | 0.3609 | |
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| 1.2649 | 13.0 | 871 | 1.8970 | 0.3383 | |
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| 1.2179 | 14.0 | 938 | 1.8429 | 0.3910 | |
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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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