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---
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license: apache-2.0
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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: hubert-base-ft-keyword-spotting
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results: []
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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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# hubert-base-ft-keyword-spotting
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This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the superb dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0774
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- Accuracy: 0.9819
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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: 32
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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: 128
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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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- 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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| 1.0422 | 1.0 | 399 | 0.8999 | 0.6918 |
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| 0.3296 | 2.0 | 798 | 0.1505 | 0.9778 |
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| 0.2088 | 3.0 | 1197 | 0.0901 | 0.9816 |
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| 0.202 | 4.0 | 1596 | 0.0848 | 0.9813 |
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| 0.1535 | 5.0 | 1995 | 0.0774 | 0.9819 |
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### Framework versions
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- Transformers 4.12.0.dev0
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- Pytorch 1.9.1+cu111
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- Datasets 1.14.0
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- Tokenizers 0.10.3
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