---
license: cc-by-nc-sa-4.0
base_model: audeering/wav2vec2-large-robust-6-ft-age-gender
tags:
- generated_from_trainer
datasets:
- SLIdataset
metrics:
- accuracy
model-index:
- name: wav2vec2-large-robust-6-ft-age-gender-finetuned-dataset
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: privateSLI
      type: SLIdataset
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9832041343669251
---

<!-- 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. -->

# wav2vec2-large-robust-6-ft-age-gender-finetuned-dataset

This model is a fine-tuned version of [audeering/wav2vec2-large-robust-6-ft-age-gender](https://huggingface.co/audeering/wav2vec2-large-robust-6-ft-age-gender) on the privateSLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0890
- Accuracy: 0.9832

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4327        | 1.0   | 289  | 0.2571          | 0.9134   |
| 0.6169        | 2.0   | 578  | 0.1431          | 0.9638   |
| 0.2803        | 3.0   | 867  | 0.2276          | 0.9561   |
| 0.1813        | 4.0   | 1156 | 0.1077          | 0.9780   |
| 0.0785        | 5.0   | 1445 | 0.0764          | 0.9832   |
| 0.0369        | 6.0   | 1734 | 0.0835          | 0.9832   |
| 0.1594        | 7.0   | 2023 | 0.0756          | 0.9845   |
| 0.129         | 8.0   | 2312 | 0.0761          | 0.9884   |
| 0.1519        | 9.0   | 2601 | 0.0682          | 0.9871   |
| 0.1179        | 10.0  | 2890 | 0.0890          | 0.9832   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3