---
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
- automatic-speech-recognition
- hf-asr-leaderboard
- pashto
- ps
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Small Pashto
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs ps_af
      type: google/fleurs
      args: 'config: ps_af, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 56.651029055690074
---

<!-- 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 Pashto

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs ps_af dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2273
- Wer: 56.6510

## 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: 3e-07
- train_batch_size: 64
- eval_batch_size: 32
- 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: 800
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 2.1183        | 3.7    | 100  | 1.3170          | 76.9522 |
| 0.8565        | 7.41   | 200  | 0.9367          | 61.9930 |
| 0.2246        | 11.11  | 300  | 0.9642          | 58.8302 |
| 0.054         | 14.81  | 400  | 1.0876          | 57.9903 |
| 0.0159        | 18.52  | 500  | 1.1798          | 57.8768 |
| 0.0045        | 22.22  | 600  | 1.2309          | 56.6510 |
| 0.0026        | 100.0  | 700  | 1.2581          | 56.8478 |
| 0.0023        | 114.29 | 800  | 1.2710          | 56.7570 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2