---
language:
- id
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Small Id - Fine Tuned - Revised
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 13
      type: mozilla-foundation/common_voice_13_0
      config: id
      split: validation
      args: id
    metrics:
    - name: Wer
      type: wer
      value: 18.470763265858167
---

<!-- 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 Small Id - Fine Tuned - Revised

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3528
- Wer Ortho: 22.8496
- Wer: 18.4708

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.3546        | 0.7911 | 250  | 0.3433          | 23.8195   | 18.6421 |
| 0.1621        | 1.5823 | 500  | 0.3325          | 23.2594   | 18.9171 |
| 0.058         | 2.3734 | 750  | 0.3483          | 23.1274   | 18.0966 |
| 0.0265        | 3.1646 | 1000 | 0.3528          | 22.8496   | 18.4708 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1