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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 |
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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: 0.8057553956834532 |
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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 |
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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: 1.0829 |
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- Accuracy: 0.8058 |
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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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| 1.8285 | 1.0 | 824 | 1.9509 | 0.7167 | |
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| 0.5292 | 2.0 | 1648 | 1.3813 | 0.7909 | |
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| 0.3554 | 3.0 | 2472 | 1.1773 | 0.7941 | |
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| 0.2873 | 4.0 | 3296 | 1.2437 | 0.7981 | |
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| 0.2525 | 5.0 | 4120 | 1.2514 | 0.8004 | |
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| 0.2941 | 6.0 | 4944 | 1.2243 | 0.7995 | |
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| 0.1809 | 7.0 | 5768 | 1.1965 | 0.8008 | |
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| 0.2313 | 8.0 | 6592 | 1.0694 | 0.8022 | |
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| 0.1917 | 9.0 | 7416 | 1.0618 | 0.7995 | |
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| 0.1212 | 10.0 | 8240 | 1.0972 | 0.8026 | |
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| 0.185 | 11.0 | 9064 | 1.0868 | 0.8017 | |
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| 0.143 | 12.0 | 9888 | 1.1558 | 0.8031 | |
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| 0.2227 | 13.0 | 10712 | 1.0550 | 0.8040 | |
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| 0.1884 | 14.0 | 11536 | 1.0384 | 0.8022 | |
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| 0.1183 | 15.0 | 12360 | 1.0169 | 0.8035 | |
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| 0.1849 | 16.0 | 13184 | 1.0061 | 0.8035 | |
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| 0.141 | 17.0 | 14008 | 1.0337 | 0.8053 | |
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| 0.1328 | 18.0 | 14832 | 1.0829 | 0.8058 | |
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| 0.1238 | 19.0 | 15656 | 1.0576 | 0.8053 | |
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| 0.0932 | 20.0 | 16480 | 1.0641 | 0.8053 | |
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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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