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README.md ADDED
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+ ---
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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: heartbeat-detection
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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: train[:90]
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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: 1.0
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+ ---
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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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+
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+ # heartbeat-detection
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+
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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: 1.0986
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+ - Accuracy: 1.0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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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: 16
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.5932 | 1.0 | 3 | 1.5907 | 0.3333 |
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+ | 1.5499 | 2.0 | 6 | 1.4593 | 1.0 |
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+ | 1.4481 | 3.0 | 9 | 1.3419 | 1.0 |
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+ | 1.3044 | 4.0 | 12 | 1.2065 | 1.0 |
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+ | 1.193 | 5.0 | 15 | 1.0986 | 1.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.3
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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