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Hemg
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dangerous-heartbeat-detection

Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Model card Files
xet
 Metrics Community
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  1. README.md +8 -5
  2. model.safetensors +1 -1
README.md CHANGED
@@ -17,7 +17,7 @@ model-index:
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  name: audiofolder
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  type: audiofolder
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  config: default
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- split: train[:80]
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  args: default
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  metrics:
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  - name: Accuracy
@@ -32,7 +32,7 @@ should probably proofread and complete it, then remove this comment. -->
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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: 1.2731
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  - Accuracy: 1.0
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  ## Model description
@@ -52,7 +52,7 @@ More information needed
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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
@@ -61,13 +61,16 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 1
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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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- | 1.6725 | 1.0 | 2 | 1.2731 | 1.0 |
 
 
 
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  ### Framework versions
 
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  name: audiofolder
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  type: audiofolder
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  config: default
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+ split: train[:90]
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  args: default
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  metrics:
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  - name: Accuracy
 
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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: 0.6583
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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: 0.0001
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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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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 4
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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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+ | 1.781 | 0.89 | 2 | 1.3484 | 1.0 |
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+ | 1.2752 | 1.78 | 4 | 0.9439 | 1.0 |
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+ | 0.911 | 2.67 | 6 | 0.7337 | 1.0 |
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+ | 0.4377 | 3.56 | 8 | 0.6583 | 1.0 |
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  ### Framework versions
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