| | --- |
| | license: apache-2.0 |
| | base_model: facebook/wav2vec2-base |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - speech_commands |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: wav2vec_final_output |
| | results: |
| | - task: |
| | name: Audio Classification |
| | type: audio-classification |
| | dataset: |
| | name: speech_commands |
| | type: speech_commands |
| | config: v0.02 |
| | split: test |
| | args: v0.02 |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.901840490797546 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # wav2vec_final_output |
| |
|
| | This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the speech_commands dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4410 |
| | - Accuracy: 0.9018 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 1.4588 | 1.0 | 663 | 1.2309 | 0.8763 | |
| | | 0.6109 | 2.0 | 1326 | 0.5745 | 0.8920 | |
| | | 0.4153 | 3.0 | 1989 | 0.4884 | 0.8953 | |
| | | 0.3227 | 4.0 | 2652 | 0.4574 | 0.8980 | |
| | | 0.2806 | 5.0 | 3315 | 0.4412 | 0.8994 | |
| | | 0.207 | 6.0 | 3978 | 0.4403 | 0.9014 | |
| | | 0.2226 | 7.0 | 4641 | 0.4479 | 0.8998 | |
| | | 0.2577 | 8.0 | 5304 | 0.4421 | 0.9014 | |
| | | 0.2188 | 9.0 | 5967 | 0.4408 | 0.9016 | |
| | | 0.2082 | 10.0 | 6630 | 0.4410 | 0.9018 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.34.1 |
| | - Pytorch 2.1.0+cu118 |
| | - Datasets 2.14.6 |
| | - Tokenizers 0.14.1 |
| | |
