---
language:
- ps
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Base Pashto - Augmented
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs
      type: google/fleurs
      config: ps_af
      split: test
      args: ps_af
    metrics:
    - name: Wer
      type: wer
      value: 57.611985472154956
---

<!-- 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 Base Pashto - Augmented

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the google/fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8723
- Wer: 57.6120
- Cer: 26.6468

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 30
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.9708        | 2.38  | 100  | 0.8821          | 64.0133 | 27.3253 |
| 0.7477        | 4.75  | 200  | 0.8062          | 59.9576 | 26.4079 |
| 0.6229        | 7.14  | 300  | 0.7855          | 58.3081 | 26.3193 |
| 0.4833        | 9.52  | 400  | 0.7870          | 57.5288 | 24.8855 |
| 0.4084        | 11.89 | 500  | 0.7980          | 56.5224 | 25.2214 |
| 0.3323        | 14.28 | 600  | 0.8201          | 56.6662 | 25.3317 |
| 0.283         | 16.66 | 700  | 0.8406          | 57.7406 | 26.8674 |
| 0.2598        | 19.05 | 800  | 0.8538          | 57.2866 | 26.0386 |
| 0.2235        | 21.42 | 900  | 0.8697          | 58.2703 | 26.6819 |
| 0.2202        | 23.8  | 1000 | 0.8723          | 57.6120 | 26.6468 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2