--- 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 --- # 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