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--- |
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base_model: microsoft/wavlm-base |
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tags: |
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- audio-classification |
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- generated_from_trainer |
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datasets: |
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- superb |
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metrics: |
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- accuracy |
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model-index: |
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- name: wav2vec2-base-ft-keyword-spotting |
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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: superb |
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type: superb |
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config: ks |
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split: validation |
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args: ks |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9694027655192704 |
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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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# wav2vec2-base-ft-keyword-spotting |
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This model is a fine-tuned version of [microsoft/wavlm-base](https://huggingface.co/microsoft/wavlm-base) on the superb dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2270 |
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- Accuracy: 0.9694 |
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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: 3e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 0 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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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: 5.0 |
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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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| 1.3203 | 1.0 | 199 | 1.2906 | 0.6328 | |
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| 0.9587 | 2.0 | 399 | 0.7793 | 0.7355 | |
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| 0.6218 | 3.0 | 599 | 0.3858 | 0.9289 | |
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| 0.4379 | 4.0 | 799 | 0.2581 | 0.9688 | |
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| 0.3779 | 4.98 | 995 | 0.2270 | 0.9694 | |
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### Framework versions |
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- Transformers 4.34.0.dev0 |
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- Pytorch 2.0.0.post302 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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