| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - minds14 |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: Audio_Classification_model |
| | results: [] |
| | --- |
| | |
| | <!-- 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_Classification_model |
| |
|
| | This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the minds14 dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.6498 |
| | - Accuracy: 0.0796 |
| |
|
| | ## 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: 10 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | No log | 0.8 | 3 | 2.6440 | 0.0619 | |
| | | No log | 1.87 | 7 | 2.6484 | 0.0442 | |
| | | 2.6344 | 2.93 | 11 | 2.6489 | 0.0619 | |
| | | 2.6344 | 4.0 | 15 | 2.6518 | 0.0619 | |
| | | 2.6344 | 4.8 | 18 | 2.6547 | 0.0531 | |
| | | 2.6173 | 5.87 | 22 | 2.6512 | 0.0531 | |
| | | 2.6173 | 6.93 | 26 | 2.6498 | 0.0796 | |
| | | 2.6098 | 8.0 | 30 | 2.6474 | 0.0531 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.27.1 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.9.0 |
| | - Tokenizers 0.13.3 |
| |
|
