---
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 Malayalam - Arjun Shaji
  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: 81.60919540229885
---

<!-- 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 Malayalam - Arjun Shaji

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: 0.7363
- Wer: 81.6092

## 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: 1000
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss | Wer     |
|:-------------:|:--------:|:----:|:---------------:|:-------:|
| 0.0433        | 18.5185  | 500  | 0.5265          | 94.7126 |
| 0.0144        | 37.0370  | 1000 | 0.5352          | 89.1954 |
| 0.0057        | 55.5556  | 1500 | 0.5989          | 87.5862 |
| 0.0004        | 74.0741  | 2000 | 0.6575          | 82.0690 |
| 0.0           | 92.5926  | 2500 | 0.6616          | 81.6092 |
| 0.0           | 111.1111 | 3000 | 0.6911          | 81.3793 |
| 0.0           | 129.6296 | 3500 | 0.7097          | 81.3793 |
| 0.0           | 148.1481 | 4000 | 0.7232          | 81.3793 |
| 0.0           | 166.6667 | 4500 | 0.7327          | 81.3793 |
| 0.0           | 185.1852 | 5000 | 0.7363          | 81.6092 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1