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---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- arrow
metrics:
- accuracy
model-index:
- name: eeem069_heart_murmur_classification
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: arrow
type: arrow
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8221153846153846
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# eeem069_heart_murmur_classification
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the arrow dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5614
- Accuracy: 0.8221
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0582 | 0.92 | 9 | 0.8806 | 0.8045 |
| 0.804 | 1.95 | 19 | 0.6482 | 0.8045 |
| 0.6425 | 2.97 | 29 | 0.6061 | 0.8045 |
| 0.6025 | 4.0 | 39 | 0.5924 | 0.8045 |
| 0.5865 | 4.92 | 48 | 0.5879 | 0.8045 |
| 0.6228 | 5.95 | 58 | 0.5834 | 0.8045 |
| 0.5676 | 6.97 | 68 | 0.5840 | 0.8045 |
| 0.5856 | 8.0 | 78 | 0.5890 | 0.8045 |
| 0.5946 | 8.92 | 87 | 0.5785 | 0.8045 |
| 0.586 | 9.95 | 97 | 0.5726 | 0.8045 |
| 0.5846 | 10.97 | 107 | 0.5723 | 0.8045 |
| 0.5545 | 12.0 | 117 | 0.5707 | 0.8237 |
| 0.5569 | 12.92 | 126 | 0.5846 | 0.8141 |
| 0.5997 | 13.95 | 136 | 0.5649 | 0.8173 |
| 0.5404 | 14.97 | 146 | 0.5625 | 0.8221 |
| 0.5438 | 16.0 | 156 | 0.5641 | 0.8189 |
| 0.5294 | 16.92 | 165 | 0.5633 | 0.8221 |
| 0.5196 | 17.95 | 175 | 0.5613 | 0.8205 |
| 0.5369 | 18.46 | 180 | 0.5614 | 0.8221 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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