---
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: 59.64817110973342
---

<!-- 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: 0.7901
- Wer: 59.6482
- Cer: 27.0947

## 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: 600
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 1.1215        | 2.38  | 100  | 0.9444          | 68.3354 | 30.2694 |
| 0.8268        | 4.75  | 200  | 0.8267          | 63.2440 | 28.2636 |
| 0.6912        | 7.14  | 300  | 0.7959          | 62.2443 | 28.2123 |
| 0.5725        | 9.52  | 400  | 0.7896          | 60.5859 | 27.6920 |
| 0.5231        | 11.89 | 500  | 0.7884          | 59.8574 | 27.1273 |
| 0.4752        | 14.28 | 600  | 0.7901          | 59.6482 | 27.0947 |


### Framework versions

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