---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-pashto
  results: []
---

<!-- 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

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4625
- Wer: 30.8805

## 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
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.008         | 0.9901 | 100  | 0.4411          | 28.5655 |
| 0.0058        | 1.9802 | 200  | 0.4440          | 28.3175 |
| 0.0073        | 2.9703 | 300  | 0.4664          | 28.9376 |
| 0.0095        | 3.9604 | 400  | 0.4832          | 30.6738 |
| 0.0148        | 4.9505 | 500  | 0.4625          | 30.8805 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.2.0
- Datasets 3.2.0
- Tokenizers 0.21.0