---
library_name: transformers
tags:
- audio-classification
- generated_from_trainer
datasets:
- voxceleb
metrics:
- accuracy
model-index:
- name: ecapa-tdnn-voxceleb1-c512-aam
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: confit/voxceleb
      type: voxceleb
      config: verification
      split: train
      args: verification
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9757901815736382
---

<!-- 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. -->

# 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: 0.5840
- Accuracy: 0.9758

## 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: 0.0005
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 9.047         | 1.0   | 575  | 8.3662          | 0.4304   |
| 5.3508        | 2.0   | 1150 | 4.0252          | 0.8191   |
| 3.3124        | 3.0   | 1725 | 2.1083          | 0.9260   |
| 2.3212        | 4.0   | 2300 | 1.2224          | 0.9435   |
| 1.6276        | 5.0   | 2875 | 0.8229          | 0.9677   |
| 1.1418        | 6.0   | 3450 | 0.5840          | 0.9758   |
| 1.0484        | 7.0   | 4025 | 0.5781          | 0.9738   |
| 0.0           | 8.0   | 4600 | nan             | 0.0007   |
| 0.0           | 9.0   | 5175 | nan             | 0.0007   |
| 0.0           | 10.0  | 5750 | nan             | 0.0007   |


### Framework versions

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