---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small Alb - Sumitesh
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_17_0
      config: sq
      split: None
      args: 'config: sq, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 52.63324873096447
language:
- sq
pipeline_tag: automatic-speech-recognition
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Small Alb - Sumitesh

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2013
- Wer: 52.6332

## Model description

This is a speech to text model finetuned over Whisper model by OpenAI.

## Intended uses & limitations

This is free to use for learning or commercial purposes. I don't plan to monetize this ever or make it private. My goal is to make whisper more localized which is why i have this model public.

## Training and evaluation data

This model is trained on common_voice_17 dataset. It is an open source multilingual dataset.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- 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_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.005         | 15.1515 | 1000 | 0.9955          | 53.7437 |
| 0.0003        | 30.3030 | 2000 | 1.1066          | 52.5698 |
| 0.0001        | 45.4545 | 3000 | 1.1585          | 52.8553 |
| 0.0001        | 60.6061 | 4000 | 1.1889          | 52.7284 |
| 0.0001        | 75.7576 | 5000 | 1.2013          | 52.6332 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1