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--- |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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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-tiny-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: 0.8039568345323741 |
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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-tiny-speech-commands |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the speech_commands dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3232 |
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- Accuracy: 0.8040 |
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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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| 0.4229 | 1.0 | 412 | 1.1286 | 0.7936 | |
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| 0.1396 | 2.0 | 824 | 1.0506 | 0.7995 | |
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| 0.1323 | 3.0 | 1236 | 1.1224 | 0.7977 | |
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| 0.0528 | 4.0 | 1648 | 1.0810 | 0.8004 | |
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| 0.0889 | 5.0 | 2060 | 0.9224 | 0.8022 | |
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| 0.076 | 6.0 | 2472 | 1.0393 | 0.7981 | |
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| 0.0429 | 7.0 | 2884 | 1.1115 | 0.7990 | |
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| 0.0007 | 8.0 | 3296 | 1.1706 | 0.8026 | |
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| 0.0129 | 9.0 | 3708 | 1.0661 | 0.8013 | |
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| 0.0161 | 10.0 | 4120 | 1.0114 | 0.7990 | |
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| 0.0205 | 11.0 | 4532 | 1.2129 | 0.8031 | |
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| 0.0107 | 12.0 | 4944 | 1.1118 | 0.8026 | |
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| 0.0099 | 13.0 | 5356 | 0.9145 | 0.8031 | |
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| 0.0002 | 14.0 | 5768 | 1.1582 | 0.7999 | |
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| 0.0001 | 15.0 | 6180 | 1.2959 | 0.8035 | |
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| 0.0163 | 16.0 | 6592 | 1.0992 | 0.8026 | |
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| 0.0001 | 17.0 | 7004 | 1.2913 | 0.8035 | |
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| 0.0003 | 18.0 | 7416 | 1.3232 | 0.8040 | |
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| 0.0001 | 19.0 | 7828 | 1.3720 | 0.8040 | |
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| 0.0001 | 20.0 | 8240 | 1.3889 | 0.8040 | |
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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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