---
library_name: transformers
language:
- ps
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 - Hanif Rahman
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0
      type: mozilla-foundation/common_voice_17_0
      config: ps
      split: test
      args: 'config: ps, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 47.980613893376415
---

<!-- 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 - Hanif Rahman

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: 0.8094
- Wer Ortho: 51.6855
- Wer: 47.9806

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 | Wer Ortho | Wer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.6754        | 0.9346 | 100  | 0.6689          | 62.1021   | 58.4888 |
| 0.4477        | 1.8692 | 200  | 0.6215          | 57.3134   | 53.5101 |
| 0.2243        | 2.8037 | 300  | 0.6222          | 55.8883   | 52.0928 |
| 0.0949        | 3.7383 | 400  | 0.6822          | 54.6007   | 49.6989 |
| 0.0448        | 4.6729 | 500  | 0.7240          | 53.5301   | 49.4346 |
| 0.0201        | 5.6075 | 600  | 0.7355          | 52.7344   | 48.9646 |
| 0.0124        | 6.5421 | 700  | 0.7615          | 52.3944   | 48.6929 |
| 0.0035        | 7.4766 | 800  | 0.7868          | 51.0778   | 47.2243 |
| 0.002         | 8.4112 | 900  | 0.8025          | 51.6276   | 47.6869 |
| 0.0011        | 9.3458 | 1000 | 0.8094          | 51.6855   | 47.9806 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3