---
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
datasets:
- common_language
metrics:
- accuracy
model-index:
- name: hubert-base-ls960-finetuned-common_language-finetuned-common_language
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: Common Language
      type: common_language
      config: full
      split: test
      args: full
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8011068254234446
---

<!-- 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. -->

# hubert-base-ls960-finetuned-common_language-finetuned-common_language

This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co./facebook/hubert-base-ls960) on the Common Language dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4164
- Accuracy: 0.8011

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.9713        | 1.0   | 2774  | 3.0764          | 0.1615   |
| 1.7443        | 2.0   | 5549  | 1.8279          | 0.4734   |
| 1.1304        | 3.0   | 8323  | 1.3202          | 0.6371   |
| 1.2718        | 4.0   | 11098 | 1.1571          | 0.6968   |
| 0.769         | 5.0   | 13872 | 1.2917          | 0.7127   |
| 0.2656        | 6.0   | 16647 | 1.1549          | 0.7479   |
| 0.2939        | 7.0   | 19421 | 1.2372          | 0.7736   |
| 0.1278        | 8.0   | 22196 | 1.2985          | 0.7875   |
| 0.5175        | 9.0   | 24970 | 1.3664          | 0.7986   |
| 0.0547        | 10.0  | 27740 | 1.4164          | 0.8011   |


### Framework versions

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