---
license: apache-2.0
base_model: facebook/wav2vec2-large
tags:
- audio-classification
- generated_from_trainer
datasets:
- superb
metrics:
- accuracy
model-index:
- name: superb_ks_42
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: superb
      type: superb
      config: ks
      split: validation
      args: ks
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9839658723153869
---

<!-- 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. -->

# superb_ks_42

This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on the superb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0856
- Accuracy: 0.9840

## 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: 32
- eval_batch_size: 4
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0646        | 1.0   | 1597  | 0.1839          | 0.9625   |
| 0.3751        | 2.0   | 3194  | 0.1954          | 0.9647   |
| 0.3156        | 3.0   | 4791  | 0.1335          | 0.9744   |
| 0.257         | 4.0   | 6388  | 0.1062          | 0.9796   |
| 0.2386        | 5.0   | 7985  | 0.1029          | 0.9801   |
| 0.2085        | 6.0   | 9582  | 0.1002          | 0.9815   |
| 0.1715        | 7.0   | 11179 | 0.1031          | 0.9818   |
| 0.1575        | 8.0   | 12776 | 0.0938          | 0.9819   |
| 0.1332        | 9.0   | 14373 | 0.0896          | 0.9831   |
| 0.1288        | 10.0  | 15970 | 0.0856          | 0.9840   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1