---
library_name: transformers
language:
- id
license: apache-2.0
base_model: kneth90/whisper-small-id-kp
tags:
- generated_from_trainer
datasets:
- kneth90/snamol_temp
metrics:
- wer
model-index:
- name: WHISPER Small KP
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: kneth90/snamol_temp
      args: 'config: hi, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 814.2857142857142
---

<!-- 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 KP

This model is a fine-tuned version of [kneth90/whisper-small-id-kp](https://huggingface.co/kneth90/whisper-small-id-kp) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4420
- Wer: 814.2857

## 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 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: 6000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.0           | 1000.0 | 1000 | 0.5975          | 7.1429   |
| 0.0           | 2000.0 | 2000 | 0.8193          | 14.2857  |
| 0.0           | 3000.0 | 3000 | 1.0415          | 50.0     |
| 0.0           | 4000.0 | 4000 | 1.3226          | 50.0     |
| 0.0           | 5000.0 | 5000 | 1.3835          | 42.8571  |
| 0.0           | 6000.0 | 6000 | 1.4420          | 814.2857 |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0