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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base-960h |
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tags: |
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- generated_from_trainer |
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datasets: |
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- audiofolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: wav2vec2-base-960h-heart-sounds |
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results: |
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- task: |
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name: Audio Classification |
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type: audio-classification |
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dataset: |
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name: audiofolder |
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type: audiofolder |
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config: default |
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split: validation |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8673780487804879 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/vldmrl-org/HeartDiseaseDetector/runs/7tntog3e) |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/vldmrl-org/HeartDiseaseDetector/runs/7tntog3e) |
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# wav2vec2-base-960h-heart-sounds |
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This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3595 |
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- Accuracy: 0.8674 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| 0.9791 | 1.0 | 83 | 0.9290 | 0.5442 | |
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| 0.6532 | 2.0 | 166 | 0.5495 | 0.8186 | |
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| 0.5202 | 3.0 | 249 | 0.4569 | 0.8216 | |
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| 0.4421 | 4.0 | 332 | 0.4378 | 0.8399 | |
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| 0.4144 | 5.0 | 415 | 0.3853 | 0.8765 | |
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| 0.4213 | 6.0 | 498 | 0.3835 | 0.8537 | |
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| 0.3819 | 7.0 | 581 | 0.3647 | 0.8674 | |
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| 0.3994 | 7.9119 | 656 | 0.3595 | 0.8674 | |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.0 |
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