---
datasets:
- voxceleb
library_name: transformers
metrics:
- accuracy
tags:
- audio-classification
- generated_from_trainer
model-index:
- name: ecapa-tdnn-voxceleb1-c512-aam
  results:
  - task:
      type: audio-classification
      name: Audio Classification
    dataset:
      name: confit/voxceleb
      type: voxceleb
      config: verification
      split: train
      args: verification
    metrics:
    - type: accuracy
      value: 0.8030272452068618
      name: Accuracy
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ecapa-tdnn-voxceleb1-c512-aam

This model is a fine-tuned version of [](https://huggingface.co/) on the confit/voxceleb dataset.
It achieves the following results on the evaluation set:
- Loss: 4.7003
- Accuracy: 0.8030

## 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: 0.0001
- train_batch_size: 256
- eval_batch_size: 1
- seed: 914
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 11.3851       | 1.0   | 523  | 11.0293         | 0.1806   |
| 9.7596        | 2.0   | 1046 | 9.1401          | 0.3850   |
| 8.7136        | 3.0   | 1569 | 7.8821          | 0.5242   |
| 7.848         | 4.0   | 2092 | 6.9451          | 0.6144   |
| 7.1912        | 5.0   | 2615 | 6.2630          | 0.6821   |
| 6.6763        | 6.0   | 3138 | 5.7182          | 0.7292   |
| 6.3112        | 7.0   | 3661 | 5.2653          | 0.7632   |
| 6.0255        | 8.0   | 4184 | 4.9663          | 0.7826   |
| 5.8091        | 9.0   | 4707 | 4.7787          | 0.7957   |
| 5.7269        | 10.0  | 5230 | 4.7003          | 0.8030   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.0.0+cu117
- Datasets 3.2.0
- Tokenizers 0.21.0