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

<!-- 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. -->

# whisper-base-finetuned-common_voice

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0319
- Accuracy: 0.9925
- F1: 0.9925
- Recall: 0.9925
- Precision: 0.9927
- Mcc: 0.9907
- Auc: 0.9999

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|:------:|:------:|
| 0.1765        | 1.0   | 200  | 0.1455          | 0.9775   | 0.9775 | 0.9775 | 0.9776    | 0.9719 | 0.9996 |
| 0.0067        | 2.0   | 400  | 0.0734          | 0.98     | 0.9800 | 0.9800 | 0.9804    | 0.9751 | 0.9996 |
| 0.0218        | 3.0   | 600  | 0.0719          | 0.9875   | 0.9875 | 0.9875 | 0.9879    | 0.9845 | 0.9999 |
| 0.002         | 4.0   | 800  | 0.1055          | 0.975    | 0.9752 | 0.975  | 0.9762    | 0.9690 | 0.9997 |
| 0.0014        | 5.0   | 1000 | 0.0312          | 0.995    | 0.9950 | 0.9950 | 0.9951    | 0.9938 | 0.9999 |
| 0.0011        | 6.0   | 1200 | 0.0305          | 0.995    | 0.9950 | 0.9950 | 0.9951    | 0.9938 | 0.9999 |
| 0.0009        | 7.0   | 1400 | 0.0310          | 0.995    | 0.9950 | 0.9950 | 0.9951    | 0.9938 | 0.9999 |
| 0.0008        | 8.0   | 1600 | 0.0315          | 0.9925   | 0.9925 | 0.9925 | 0.9927    | 0.9907 | 0.9999 |
| 0.0008        | 9.0   | 1800 | 0.0318          | 0.9925   | 0.9925 | 0.9925 | 0.9927    | 0.9907 | 0.9999 |
| 0.0007        | 10.0  | 2000 | 0.0319          | 0.9925   | 0.9925 | 0.9925 | 0.9927    | 0.9907 | 0.9999 |


### Framework versions

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