---
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: 0.2002
- Accuracy: 0.955
- F1: 0.9549
- Recall: 0.9550
- Precision: 0.9551
- Mcc: 0.9438
- Auc: 0.9942

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|:------:|:------:|
| 1.5544        | 1.0   | 200  | 1.5193          | 0.405    | 0.3628 | 0.4050 | 0.5940    | 0.2904 | 0.8407 |
| 1.1406        | 2.0   | 400  | 0.9811          | 0.6375   | 0.5780 | 0.6375 | 0.6712    | 0.5734 | 0.9464 |
| 0.7902        | 3.0   | 600  | 0.6775          | 0.8125   | 0.7969 | 0.8125 | 0.8181    | 0.7740 | 0.9724 |
| 0.5346        | 4.0   | 800  | 0.5083          | 0.8725   | 0.8683 | 0.8725 | 0.8774    | 0.8438 | 0.9834 |
| 0.5139        | 5.0   | 1000 | 0.3943          | 0.9025   | 0.8988 | 0.9025 | 0.9074    | 0.8809 | 0.9879 |
| 0.5136        | 6.0   | 1200 | 0.3314          | 0.915    | 0.9145 | 0.915  | 0.9174    | 0.8945 | 0.9881 |
| 0.3726        | 7.0   | 1400 | 0.2894          | 0.925    | 0.9241 | 0.925  | 0.9258    | 0.9069 | 0.9878 |
| 0.3072        | 8.0   | 1600 | 0.2267          | 0.9325   | 0.9314 | 0.9325 | 0.9349    | 0.9167 | 0.9914 |
| 0.1948        | 9.0   | 1800 | 0.2117          | 0.945    | 0.9445 | 0.945  | 0.9461    | 0.9317 | 0.9931 |
| 0.2312        | 10.0  | 2000 | 0.2002          | 0.955    | 0.9549 | 0.9550 | 0.9551    | 0.9438 | 0.9942 |


### Framework versions

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