--- 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: 0.035398230088495575 --- # 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: 2.6657 - Accuracy: 0.0354 ## 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 | 0.0442 | | No log | 1.8667 | 7 | 2.6488 | 0.0442 | | 2.6318 | 2.9333 | 11 | 2.6509 | 0.0354 | | 2.6318 | 4.0 | 15 | 2.6575 | 0.0354 | | 2.6318 | 4.8 | 18 | 2.6600 | 0.0442 | | 2.6186 | 5.8667 | 22 | 2.6634 | 0.0354 | | 2.6186 | 6.9333 | 26 | 2.6657 | 0.0354 | | 2.6115 | 8.0 | 30 | 2.6657 | 0.0354 | ### Framework versions - Transformers 4.45.2 - Pytorch 2.4.1 - Datasets 3.0.1 - Tokenizers 0.20.1