| --- |
| license: apache-2.0 |
| base_model: facebook/wav2vec2-base |
| tags: |
| - generated_from_trainer |
| datasets: |
| - audiofolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: model_KWS |
| results: |
| - task: |
| name: Audio Classification |
| type: audio-classification |
| dataset: |
| name: audiofolder |
| type: audiofolder |
| config: default |
| split: test |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.9825 |
| --- |
| |
| <!-- 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. --> |
|
|
| # model_KWS |
| |
| This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3346 |
| - Accuracy: 0.9825 |
| |
| ## Model description |
| |
| Finetuned on custom commands: "ambient", "light", "off", "on", "scene1", "scene2", "scene3", "void" |
| |
| ## Intended uses & limitations |
| |
| Intended for keyword spotting applications. |
| |
| ## Training and evaluation data |
| |
| 3200 training samples, 800 testing samples in total. |
| Originally was recorded 20 samples of every class. |
| Each sample was randomly augmented with random methods: pitch-shifting, time-stretching, volume-change, gaussian noise. |
| |
| ## 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: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 2.0119 | 1.0 | 25 | 1.9832 | 0.375 | |
| | 1.4505 | 2.0 | 50 | 1.3361 | 0.8337 | |
| | 1.0767 | 3.0 | 75 | 0.8700 | 0.955 | |
| | 0.7448 | 4.0 | 100 | 0.6919 | 0.9513 | |
| | 0.6143 | 5.0 | 125 | 0.5333 | 0.9625 | |
| | 0.4924 | 6.0 | 150 | 0.4387 | 0.98 | |
| | 0.4544 | 7.0 | 175 | 0.3844 | 0.985 | |
| | 0.3888 | 8.0 | 200 | 0.3668 | 0.9812 | |
| | 0.3734 | 9.0 | 225 | 0.3436 | 0.9825 | |
| | 0.3522 | 10.0 | 250 | 0.3346 | 0.9825 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.31.0 |
| - Pytorch 2.0.1 |
| - Datasets 2.14.0 |
| - Tokenizers 0.13.3 |
| |
