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---
license: apache-2.0
base_model: facebook/hubert-large-ll60k
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
should probably proofread and complete it, then remove this comment. -->

# superb_ks_42

This model is a fine-tuned version of [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) on the superb dataset.
It achieves the following results on the evaluation set:
- Loss: -9.0111
- Accuracy: 0.6209
- Test Accuracy: 0.6209
- Df Accuracy: 0.1395
- Unlearn Overall Accuracy: 0.7407
- Unlearn Time: 929.3382

## 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: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----------------:|:------------------------:|:----:|
| No log        | 1.0   | 128  | -9.0111         | 0.1395   | 0.7407           | 0.7407                   | -1   |
| No log        | 2.0   | 256  | -20.9958        | 0.1395   | 0.7407           | 0.7407                   | -1   |
| No log        | 3.0   | 384  | -35.4087        | 0.1395   | 0.7407           | 0.7407                   | -1   |
| No log        | 4.0   | 512  | -51.3901        | 0.1395   | 0.7407           | 0.7407                   | -1   |
| No log        | 5.0   | 640  | -67.7050        | 0.1395   | 0.7407           | 0.7407                   | -1   |
| No log        | 6.0   | 768  | -83.0873        | 0.1395   | 0.7407           | 0.7407                   | -1   |
| No log        | 7.0   | 896  | -96.3518        | 0.1395   | 0.7407           | 0.7407                   | -1   |
| -113.6834     | 8.0   | 1024 | -106.5309       | 0.1395   | 0.7407           | 0.7407                   | -1   |
| -113.6834     | 9.0   | 1152 | -112.9372       | 0.1395   | 0.7407           | 0.7407                   | -1   |
| -113.6834     | 10.0  | 1280 | -115.1336       | 0.1395   | 0.7407           | 0.7407                   | -1   |


### Framework versions

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