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--- |
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license: apache-2.0 |
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base_model: facebook/hubert-base-ls960 |
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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: hubert-base-ls960-speech-commands-h |
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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_commands |
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type: speech_commands |
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config: v0.02 |
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split: None |
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args: v0.02 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7594424460431655 |
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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-ls960-speech-commands-h |
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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 speech_commands dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3148 |
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- Accuracy: 0.7594 |
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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: 48 |
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- eval_batch_size: 48 |
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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: 20 |
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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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| 2.743 | 1.0 | 824 | 3.4107 | 0.1781 | |
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| 2.3383 | 2.0 | 1648 | 3.4632 | 0.1862 | |
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| 2.2702 | 3.0 | 2472 | 3.5701 | 0.0787 | |
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| 2.3059 | 4.0 | 3296 | 3.5742 | 0.0971 | |
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| 2.2574 | 5.0 | 4120 | 3.5457 | 0.1493 | |
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| 2.0617 | 6.0 | 4944 | 2.8490 | 0.3453 | |
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| 2.0289 | 7.0 | 5768 | 2.7607 | 0.3215 | |
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| 1.7807 | 8.0 | 6592 | 2.5721 | 0.4681 | |
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| 1.8188 | 9.0 | 7416 | 2.5625 | 0.5301 | |
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| 1.3812 | 10.0 | 8240 | 2.4258 | 0.6942 | |
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| 1.3136 | 11.0 | 9064 | 2.2087 | 0.6884 | |
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| 1.2867 | 12.0 | 9888 | 1.8347 | 0.7221 | |
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| 1.1036 | 13.0 | 10712 | 1.6731 | 0.7383 | |
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| 0.9534 | 14.0 | 11536 | 1.8732 | 0.7307 | |
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| 0.9289 | 15.0 | 12360 | 1.5742 | 0.7415 | |
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| 1.0973 | 16.0 | 13184 | 1.3693 | 0.7365 | |
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| 0.989 | 17.0 | 14008 | 1.2718 | 0.7455 | |
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| 0.8876 | 18.0 | 14832 | 1.3148 | 0.7594 | |
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| 0.814 | 19.0 | 15656 | 1.2231 | 0.7558 | |
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| 0.9899 | 20.0 | 16480 | 1.2349 | 0.7522 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.19.1 |
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