---
library_name: transformers
license: mit
datasets:
- Tarakeshwaran/Whisper-train-data
language:
- en
metrics:
- wer
base_model:
- openai/whisper-small
pipeline_tag: automatic-speech-recognition
tags:
- generated_from_trainer
model-index:
- name: Whisper Small En - Tarakeshwaran
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: minimal_common_voice_en
      type: Tarakeshwaran/Whisper-train-data
      args: 'config: en, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 13.170732
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Small En - Tarakeshwaran

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the minimal_common_voice_en dataset.
It achieves the following results on the evaluation set:
- Loss: 1.041972
- Wer: 	13.170732

## 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: adamw_bnb_8bit
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 25
- training_steps: 100
- mixed_precision_training: Native AMP


### Framework versions

- Transformers 4.47.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3