---
library_name: transformers
language:
- id
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- kneth90/test_data_set_2
metrics:
- wer
model-index:
- name: Whisper Small ID - Kenn
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Test Dataset 2
      type: kneth90/test_data_set_2
      args: 'config: hi, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 62.0253164556962
---

<!-- 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 ID - Kenn

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Test Dataset 2 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5890
- Wer: 62.0253

## 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss | Wer     |
|:-------------:|:--------:|:----:|:---------------:|:-------:|
| 0.0012        | 41.6667  | 1000 | 1.4854          | 64.1350 |
| 0.0001        | 83.3333  | 2000 | 1.5412          | 62.2363 |
| 0.0           | 125.0    | 3000 | 1.5755          | 62.0253 |
| 0.0           | 166.6667 | 4000 | 1.5890          | 62.0253 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0