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--- |
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datasets: |
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- voxceleb |
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library_name: transformers |
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metrics: |
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- accuracy |
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tags: |
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- audio-classification |
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- generated_from_trainer |
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model-index: |
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- name: ecapa-tdnn-voxceleb1-c512-aam |
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results: |
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- task: |
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type: audio-classification |
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name: Audio Classification |
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dataset: |
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name: confit/voxceleb |
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type: voxceleb |
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config: verification |
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split: train |
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args: verification |
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metrics: |
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- type: accuracy |
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value: 0.8030272452068618 |
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name: Accuracy |
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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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# ecapa-tdnn-voxceleb1-c512-aam |
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This model is a fine-tuned version of [](https://huggingface.co/) on the confit/voxceleb dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.7003 |
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- Accuracy: 0.8030 |
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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: 0.0001 |
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- train_batch_size: 256 |
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- eval_batch_size: 1 |
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- seed: 914 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10.0 |
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- mixed_precision_training: Native AMP |
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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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| 11.3851 | 1.0 | 523 | 11.0293 | 0.1806 | |
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| 9.7596 | 2.0 | 1046 | 9.1401 | 0.3850 | |
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| 8.7136 | 3.0 | 1569 | 7.8821 | 0.5242 | |
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| 7.848 | 4.0 | 2092 | 6.9451 | 0.6144 | |
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| 7.1912 | 5.0 | 2615 | 6.2630 | 0.6821 | |
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| 6.6763 | 6.0 | 3138 | 5.7182 | 0.7292 | |
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| 6.3112 | 7.0 | 3661 | 5.2653 | 0.7632 | |
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| 6.0255 | 8.0 | 4184 | 4.9663 | 0.7826 | |
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| 5.8091 | 9.0 | 4707 | 4.7787 | 0.7957 | |
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| 5.7269 | 10.0 | 5230 | 4.7003 | 0.8030 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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