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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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- speech-commands |
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metrics: |
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- accuracy |
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model-index: |
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- name: distilhubert-finetuned-speech_commands |
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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: Speech_command_RK |
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type: speech-commands |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9975728155339806 |
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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-speech_commands |
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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the Speech_command_RK dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1895 |
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- Accuracy: 0.9976 |
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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: 264 |
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- eval_batch_size: 264 |
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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: 0.1 |
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- num_epochs: 5 |
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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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| 2.1911 | 1.0 | 25 | 1.9352 | 0.8859 | |
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| 1.0366 | 2.0 | 50 | 0.8334 | 0.9915 | |
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| 0.4879 | 3.0 | 75 | 0.3774 | 0.9939 | |
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| 0.297 | 4.0 | 100 | 0.2254 | 0.9951 | |
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| 0.2422 | 5.0 | 125 | 0.1895 | 0.9976 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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