--- library_name: transformers license: apache-2.0 base_model: facebook/wav2vec2-base tags: - generated_from_trainer datasets: - minds14 metrics: - accuracy model-index: - name: my_awesome_mind_model results: - task: name: Audio Classification type: audio-classification dataset: name: minds14 type: minds14 config: en-US split: train args: en-US metrics: - name: Accuracy type: accuracy value: 0.07079646017699115 --- # my_awesome_mind_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: 2.6455 - Accuracy: 0.0708 ## 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 | 2.6377 | 0.0796 | | No log | 1.8667 | 7 | 2.6416 | 0.0619 | | 2.6367 | 2.9333 | 11 | 2.6396 | 0.0708 | | 2.6367 | 4.0 | 15 | 2.6419 | 0.0885 | | 2.6367 | 4.8 | 18 | 2.6448 | 0.0708 | | 2.6243 | 5.8667 | 22 | 2.6460 | 0.0619 | | 2.6243 | 6.9333 | 26 | 2.6459 | 0.0619 | | 2.6205 | 8.0 | 30 | 2.6455 | 0.0708 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1