metadata
library_name: transformers
tags:
- audio-classification
- generated_from_trainer
datasets:
- voxceleb
metrics:
- accuracy
model-index:
- name: aam-len3-bs256-lr1e-3
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: 0.9616548940464178
aam-len3-bs256-lr1e-3
This model is a fine-tuned version of on the confit/voxceleb dataset. It achieves the following results on the evaluation set:
- Loss: 0.6434
- Accuracy: 0.9617
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: 0.001
- 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 |
|---|---|---|---|---|
| 7.6771 | 1.0 | 523 | 6.7010 | 0.6003 |
| 3.5879 | 2.0 | 1046 | 1.9993 | 0.9141 |
| 1.9536 | 3.0 | 1569 | 0.8234 | 0.9607 |
| 1.5008 | 4.0 | 2092 | 0.6434 | 0.9617 |
| 0.0 | 5.0 | 2615 | nan | 0.0005 |
| 0.0 | 6.0 | 3138 | nan | 0.0005 |
| 0.0 | 7.0 | 3661 | nan | 0.0005 |
| 0.0 | 8.0 | 4184 | nan | 0.0005 |
| 0.0 | 9.0 | 4707 | nan | 0.0005 |
| 0.0 | 10.0 | 5230 | nan | 0.0005 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.0.0+cu117
- Datasets 3.2.0
- Tokenizers 0.21.0