---
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Tiny Pashto
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs ps_af
      type: google/fleurs
      config: ps_af
      split: test
      args: ps_af
    metrics:
    - name: Wer
      type: wer
      value: 60.05599273607748
---

<!-- 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 Tiny Pashto

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co./openai/whisper-base) on the google/fleurs ps_af dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8710
- Wer: 60.0560

## 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: 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: 30
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.9153        | 2.5   | 100  | 1.0240          | 68.9864 |
| 0.6865        | 5.0   | 200  | 0.8968          | 61.7660 |
| 0.5474        | 7.5   | 300  | 0.8744          | 60.5554 |
| 0.4646        | 10.0  | 400  | 0.8710          | 60.0560 |
| 0.4557        | 12.5  | 500  | 0.8732          | 59.4658 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2