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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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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: dysarthria_classification |
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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 |
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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: 0.175 |
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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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# dysarthria_classification |
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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: 1.3926 |
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- Accuracy: 0.175 |
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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: 3e-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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 10 |
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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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| No log | 1.0 | 3 | 1.3941 | 0.2 | |
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| No log | 2.0 | 6 | 1.3945 | 0.2 | |
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| No log | 3.0 | 9 | 1.3938 | 0.2 | |
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| 1.384 | 4.0 | 12 | 1.3934 | 0.15 | |
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| 1.384 | 5.0 | 15 | 1.3934 | 0.15 | |
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| 1.384 | 6.0 | 18 | 1.3935 | 0.15 | |
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| 1.3825 | 7.0 | 21 | 1.3930 | 0.15 | |
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| 1.3825 | 8.0 | 24 | 1.3927 | 0.15 | |
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| 1.3825 | 9.0 | 27 | 1.3926 | 0.175 | |
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| 1.3833 | 10.0 | 30 | 1.3926 | 0.175 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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