transformers tensorboard safetensors wav2vec2 audio-classification generated_from_trainer dataset:superb base_model:facebook/wav2vec2-base license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- superb
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-ks
  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: 0.9824948514268903
---

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# wav2vec2-base-finetuned-ks

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the superb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0847
- Accuracy: 0.9825

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6047        | 1.0   | 399  | 0.5085          | 0.9584   |
| 0.2681        | 2.0   | 798  | 0.1793          | 0.9747   |
| 0.2149        | 3.0   | 1197 | 0.1114          | 0.9797   |
| 0.2038        | 4.0   | 1597 | 0.0899          | 0.9815   |
| 0.1573        | 5.0   | 1995 | 0.0847          | 0.9825   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
