Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use Hemg/dangerous-heartbeat-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hemg/dangerous-heartbeat-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Hemg/dangerous-heartbeat-detection")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Hemg/dangerous-heartbeat-detection") model = AutoModelForAudioClassification.from_pretrained("Hemg/dangerous-heartbeat-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model save
Browse files- README.md +6 -6
- model.safetensors +1 -1
README.md
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 1.0
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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### Framework versions
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2805
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- Accuracy: 1.0
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0003
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.8144 | 0.89 | 2 | 1.4061 | 1.0 |
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| 1.2223 | 1.78 | 4 | 0.6946 | 1.0 |
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| 0.5897 | 2.67 | 6 | 0.3691 | 1.0 |
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| 0.2163 | 3.56 | 8 | 0.2805 | 1.0 |
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### Framework versions
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model.safetensors
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