| | --- |
| | license: apache-2.0 |
| | base_model: facebook/wav2vec2-base |
| | tags: |
| | - audio-classification |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: wav2vec2-present |
| | 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. --> |
| |
|
| | # wav2vec2-present |
| |
|
| | This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the MatsRooth/object dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0866 |
| | - Accuracy: 0.9853 |
| |
|
| | ## 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: 4 |
| | - eval_batch_size: 4 |
| | - seed: 0 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 8 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 10.0 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | | 0.5208 | 1.0 | 1539 | 0.2246 | 0.9425 | |
| | | 0.1232 | 2.0 | 3079 | 0.1606 | 0.9655 | |
| | | 0.2855 | 3.0 | 4618 | 0.1177 | 0.9696 | |
| | | 0.2405 | 4.0 | 6158 | 0.1015 | 0.9793 | |
| | | 0.0272 | 5.0 | 7697 | 0.0853 | 0.9830 | |
| | | 0.1269 | 6.0 | 9237 | 0.1081 | 0.9807 | |
| | | 0.031 | 7.0 | 10776 | 0.0811 | 0.9848 | |
| | | 0.0781 | 8.0 | 12316 | 0.0707 | 0.9848 | |
| | | 0.0317 | 9.0 | 13855 | 0.0851 | 0.9848 | |
| | | 0.068 | 10.0 | 15390 | 0.0866 | 0.9853 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.36.0.dev0 |
| | - Pytorch 2.9.0+cu128 |
| | - Datasets 2.13.1 |
| | - Tokenizers 0.15.0 |
| |
|
