---
library_name: transformers
language:
- ks
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- muneebharoon/whisper-kashmiri
metrics:
- wer
model-index:
- name: Whisper Small ks - Muneeb Haroon
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: whisper-kashmiri
      type: muneebharoon/whisper-kashmiri
      args: 'config: ks, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 39.80769230769231
---

<!-- 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 ks - Muneeb Haroon

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the whisper-kashmiri dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1578
- Wer: 39.8077

## 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: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step  | Validation Loss | Wer     |
|:-------------:|:--------:|:-----:|:---------------:|:-------:|
| 0.0123        | 21.2811  | 1000  | 0.9382          | 48.125  |
| 0.0051        | 42.5622  | 2000  | 0.9946          | 42.4519 |
| 0.0032        | 63.8432  | 3000  | 1.0278          | 41.3942 |
| 0.0           | 85.1081  | 4000  | 1.1138          | 40.5288 |
| 0.0           | 106.3892 | 5000  | 1.1578          | 39.8077 |
| 0.0           | 127.6703 | 6000  | 1.1869          | 39.8077 |
| 0.0           | 148.9514 | 7000  | 1.2211          | 40.0    |
| 0.0           | 170.2162 | 8000  | 1.2430          | 40.2404 |
| 0.0           | 191.4973 | 9000  | 1.2679          | 40.2885 |
| 0.0           | 212.7784 | 10000 | 1.2762          | 40.3365 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0