---
license: apache-2.0
base_model: steja/whisper-small-persian
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: pashto-asr-cws-v1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: fleurs
      type: fleurs
      config: ps_af
      split: None
      args: ps_af
    metrics:
    - name: Wer
      type: wer
      value: 49.37953995157385
---

<!-- 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. -->

# pashto-asr-cws-v1

This model is a fine-tuned version of [steja/whisper-small-persian](https://huggingface.co./steja/whisper-small-persian) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7501
- Wer: 49.3795
- Cer: 20.8766

## 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: 32
- eval_batch_size: 16
- 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: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|
| 0.7899        | 0.8065 | 100  | 0.8629          | 75.8323 | 47.9045 |
| 0.5051        | 1.6129 | 200  | 0.6860          | 52.9888 | 23.1242 |
| 0.3555        | 2.4194 | 300  | 0.6612          | 51.6798 | 22.9404 |
| 0.257         | 3.2258 | 400  | 0.6565          | 49.2660 | 21.0588 |
| 0.2174        | 4.0323 | 500  | 0.6560          | 47.1777 | 19.8523 |
| 0.1626        | 4.8387 | 600  | 0.6787          | 48.7591 | 20.4305 |
| 0.1268        | 5.6452 | 700  | 0.7062          | 49.4401 | 21.0137 |
| 0.0871        | 6.4516 | 800  | 0.7279          | 49.2433 | 20.7062 |
| 0.0685        | 7.2581 | 900  | 0.7443          | 49.3795 | 21.2276 |
| 0.0662        | 8.0645 | 1000 | 0.7501          | 49.3795 | 20.8766 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1