---
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: hubert-base-ls960-finetuned-common_voice
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hubert-base-ls960-finetuned-common_voice

This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0451
- Accuracy: 0.99
- F1: 0.9900
- Recall: 0.99
- Precision: 0.9900
- Mcc: 0.9875
- Auc: 0.9994

## 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: 1e-05
- train_batch_size: 8
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision | Mcc    | Auc    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|:------:|:------:|
| 0.2557        | 1.0   | 200  | 0.1431          | 0.965    | 0.9647 | 0.9650 | 0.9676    | 0.9570 | 0.9965 |
| 0.1858        | 2.0   | 400  | 0.0567          | 0.985    | 0.9849 | 0.985  | 0.9854    | 0.9814 | 0.9994 |
| 0.0626        | 3.0   | 600  | 0.0612          | 0.9875   | 0.9875 | 0.9875 | 0.9876    | 0.9844 | 0.9996 |
| 0.2167        | 4.0   | 800  | 0.0340          | 0.995    | 0.9950 | 0.9950 | 0.9950    | 0.9938 | 0.9999 |
| 0.0217        | 5.0   | 1000 | 0.0454          | 0.9925   | 0.9925 | 0.9925 | 0.9925    | 0.9906 | 0.9997 |
| 0.1366        | 6.0   | 1200 | 0.0659          | 0.985    | 0.9850 | 0.985  | 0.9852    | 0.9813 | 0.9992 |
| 0.0167        | 7.0   | 1400 | 0.0515          | 0.9925   | 0.9925 | 0.9925 | 0.9927    | 0.9907 | 0.9991 |
| 0.015         | 8.0   | 1600 | 0.0414          | 0.9925   | 0.9925 | 0.9925 | 0.9927    | 0.9907 | 0.9993 |
| 0.0312        | 9.0   | 1800 | 0.0432          | 0.9925   | 0.9925 | 0.9925 | 0.9926    | 0.9906 | 0.9993 |
| 0.0091        | 10.0  | 2000 | 0.0451          | 0.99     | 0.9900 | 0.99   | 0.9900    | 0.9875 | 0.9994 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1