---
library_name: transformers
language:
- ka
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper ka
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Subtitri voice 0.1v
      type: mozilla-foundation/common_voice_11_0
      config: ka
      split: test
      args: 'config: ka, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 42.44341950016089
---

<!-- 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 ka

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Subtitri voice 0.1v dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1584
- Wer: 42.4434

## 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     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0471        | 2.9070  | 1000 | 0.0875          | 46.0260 |
| 0.0058        | 5.8140  | 2000 | 0.1194          | 44.0363 |
| 0.0004        | 8.7209  | 3000 | 0.1400          | 42.8457 |
| 0.0001        | 11.6279 | 4000 | 0.1529          | 42.5829 |
| 0.0           | 14.5349 | 5000 | 0.1584          | 42.4434 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0