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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-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: 0.9826419535157399 |
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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 [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the superb dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0954 |
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- Accuracy: 0.9826 |
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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: 48 |
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- eval_batch_size: 32 |
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- seed: 0 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 192 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 8.0 |
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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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| 1.3624 | 1.0 | 267 | 1.1959 | 0.6546 | |
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| 0.3854 | 2.0 | 534 | 0.2675 | 0.9734 | |
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| 0.2473 | 3.0 | 801 | 0.1461 | 0.9768 | |
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| 0.1997 | 4.0 | 1068 | 0.1088 | 0.9804 | |
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| 0.1723 | 5.0 | 1335 | 0.0954 | 0.9826 | |
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| 0.1442 | 6.0 | 1602 | 0.0927 | 0.9813 | |
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| 0.1397 | 7.0 | 1869 | 0.0892 | 0.9812 | |
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| 0.1368 | 7.9728 | 2128 | 0.0896 | 0.9812 | |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.6.0+cu118 |
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- Datasets 3.3.1 |
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- Tokenizers 0.21.0 |
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