---
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: 0.6209179170344219
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 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: 414.7518
- Accuracy: 0.6209
- Test Accuracy: 0.6209
- Df Accuracy: 0.1343
- Unlearn Overall Accuracy: 0.7433
- Unlearn Time: 1648.8392

## 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: 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: 2.5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----------------:|:------------------------:|:----:|
| 0.0           | 1.0   | 1503 | 414.7518        | 0.1343   | 0.7433           | 0.7433                   | -1   |
| 0.0           | 2.0   | 3006 | 1072.2520       | 0.1343   | 0.7433           | 0.7433                   | -1   |
| 0.0           | 2.5   | 3758 | 1184.3600       | 0.1343   | 0.7433           | 0.7433                   | -1   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2