Model save
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README.md
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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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<!-- 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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# heartbeat-detection
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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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## 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: 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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### Training results
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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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### Framework versions
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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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model.safetensors
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runs/Apr04_06-02-51_cc68affaad08/events.out.tfevents.1712210571.cc68affaad08.143.1
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