| --- |
| license: apache-2.0 |
| base_model: facebook/wav2vec2-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: wave2vec2_capstone |
| results: [] |
| datasets: |
| - mozilla-foundation/common_voice_16_1 |
| language: |
| - en |
| - ca |
| - rw |
| - be |
| - eo |
| - de |
| - fr |
| - ka |
| - es |
| - lg |
| - sw |
| - fa |
| - it |
| - mh |
| - zh |
| - ba |
| - ta |
| - ru |
| - eu |
| - th |
| - pt |
| - pl |
| - ja |
| pipeline_tag: audio-classification |
| --- |
| |
|
|
| # wave2vec2_capstone |
| |
| This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the common_voice_16_1 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2796 |
| - Accuracy: 0.9400 |
| - F1 score: 0.9399 |
|
|
| ## 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: 0.0003 |
| - train_batch_size: 9 |
| - eval_batch_size: 9 |
| - seed: 42 |
| - gradient_accumulation_steps: 12 |
| - total_train_batch_size: 108 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 8 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 score | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| |
| | 0.8951 | 1.0 | 776 | 1.1617 | 0.6651 | 0.6607 | |
| | 0.6608 | 2.0 | 1552 | 0.6345 | 0.8188 | 0.8188 | |
| | 0.4426 | 3.0 | 2328 | 0.4792 | 0.8672 | 0.8677 | |
| | 0.3576 | 4.0 | 3105 | 0.3826 | 0.8917 | 0.8929 | |
| | 0.194 | 5.0 | 3881 | 0.3255 | 0.9125 | 0.9130 | |
| | 0.1635 | 6.0 | 4657 | 0.2903 | 0.9208 | 0.9206 | |
| | 0.0903 | 7.0 | 5433 | 0.2990 | 0.9300 | 0.9299 | |
| | 0.0405 | 8.0 | 6208 | 0.2796 | 0.9400 | 0.9399 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.36.2 |
| - Pytorch 2.1.2+cu121 |
| - Datasets 2.16.0 |
| - Tokenizers 0.15.0 |
|
|
