| --- |
| license: bsd-3-clause |
| base_model: MIT/ast-finetuned-speech-commands-v2 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - speech_commands |
| metrics: |
| - accuracy |
| model-index: |
| - name: audio-commands |
| results: |
| - task: |
| name: Audio Classification |
| type: audio-classification |
| dataset: |
| name: speech_commands |
| type: speech_commands |
| config: v0.03 |
| split: test |
| args: v0.03 |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.9256316218418907 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # audio-commands |
|
|
| This model is a fine-tuned version of [MIT/ast-finetuned-speech-commands-v2](https://huggingface.co/MIT/ast-finetuned-speech-commands-v2) on the speech_commands dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3977 |
| - Accuracy: 0.9256 |
| |
| ## Model description |
| |
| More information needed |
| |
| ## Intended uses & limitations |
| |
| More information needed |
| |
| ## Training and evaluation data |
| |
| More information needed |
| |
| ## Training procedure |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - learning_rate: 3e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 128 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 20 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | 0.0581 | 1.0 | 663 | 0.4816 | 0.8975 | |
| | 0.0454 | 2.0 | 1326 | 0.4184 | 0.9024 | |
| | 0.0404 | 3.0 | 1989 | 0.4361 | 0.9010 | |
| | 0.025 | 4.0 | 2653 | 0.4368 | 0.9016 | |
| | 0.0169 | 5.0 | 3316 | 0.3692 | 0.9173 | |
| | 0.0173 | 6.0 | 3979 | 0.4131 | 0.9173 | |
| | 0.0096 | 7.0 | 4642 | 0.3800 | 0.9177 | |
| | 0.0022 | 8.0 | 5306 | 0.3535 | 0.9264 | |
| | 0.0031 | 9.0 | 5969 | 0.3241 | 0.9315 | |
| | 0.0008 | 10.0 | 6632 | 0.3697 | 0.9236 | |
| | 0.0002 | 11.0 | 7295 | 0.4189 | 0.9173 | |
| | 0.001 | 12.0 | 7959 | 0.3206 | 0.9287 | |
| | 0.0003 | 13.0 | 8622 | 0.3794 | 0.9205 | |
| | 0.0003 | 14.0 | 9285 | 0.3999 | 0.9199 | |
| | 0.0 | 15.0 | 9948 | 0.4002 | 0.9220 | |
| | 0.0 | 16.0 | 10612 | 0.3896 | 0.9248 | |
| | 0.0001 | 17.0 | 11275 | 0.3930 | 0.9248 | |
| | 0.0 | 18.0 | 11938 | 0.3952 | 0.9254 | |
| | 0.0 | 19.0 | 12601 | 0.3971 | 0.9254 | |
| | 0.0 | 19.99 | 13260 | 0.3977 | 0.9256 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.38.2 |
| - Pytorch 2.1.2+cu121 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.2 |
| |
