---
language:
- ml
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 Small manju Mal
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: ml
      split: None
      args: 'config: ml, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 99.08045977011494
---

<!-- 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 manju Mal

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7138
- Wer: 99.0805

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 6000

### Training results

| Training Loss | Epoch    | Step | Validation Loss | Wer      |
|:-------------:|:--------:|:----:|:---------------:|:--------:|
| 0.0069        | 37.0370  | 1000 | 0.6246          | 145.0575 |
| 0.0025        | 74.0741  | 2000 | 0.6177          | 99.3103  |
| 0.0           | 111.1111 | 3000 | 0.6737          | 101.3793 |
| 0.0           | 148.1481 | 4000 | 0.6957          | 99.0805  |
| 0.0           | 185.1852 | 5000 | 0.7087          | 99.3103  |
| 0.0           | 222.2222 | 6000 | 0.7138          | 99.0805  |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1