---
language:
- ps
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Small Pashto - Augmented
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs
      type: google/fleurs
      args: 'config: ps_af, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 53.62439467312349
---

<!-- 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 - Augmented

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6979
- Wer: 53.6244
- Cer: 22.6847

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 30
- training_steps: 300
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      | Cer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 0.9683        | 1.19  | 100  | 0.8812          | 139.3765 | 131.6166 |
| 0.6848        | 2.38  | 200  | 0.7543          | 145.9973 | 151.3369 |
| 0.5548        | 3.57  | 300  | 0.6979          | 53.6244  | 22.6847  |


### Framework versions

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