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--- |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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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: whisper-base-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: 0.8066546762589928 |
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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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# whisper-base-speech-commands |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the speech_commands dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1307 |
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- Accuracy: 0.8067 |
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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: 96 |
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- eval_batch_size: 96 |
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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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| 0.2604 | 1.0 | 412 | 1.0617 | 0.7977 | |
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| 0.1168 | 2.0 | 824 | 1.0024 | 0.8017 | |
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| 0.1527 | 3.0 | 1236 | 0.9757 | 0.8022 | |
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| 0.0637 | 4.0 | 1648 | 1.0066 | 0.8004 | |
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| 0.0631 | 5.0 | 2060 | 1.0504 | 0.8053 | |
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| 0.0554 | 6.0 | 2472 | 1.1307 | 0.8067 | |
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| 0.1075 | 7.0 | 2884 | 1.1664 | 0.8017 | |
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| 0.021 | 8.0 | 3296 | 1.4746 | 0.8044 | |
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| 0.0144 | 9.0 | 3708 | 1.3729 | 0.8044 | |
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| 0.0158 | 10.0 | 4120 | 1.3561 | 0.8040 | |
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| 0.0504 | 11.0 | 4532 | 1.3289 | 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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