---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: whisper-small-malayalam-colab-CV17.0
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: ml
      split: test
      args: ml
    metrics:
    - name: Wer
      type: wer
      value: 0.6534493874919407
---

<!-- 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-colab-CV17.0

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3197
- Wer: 0.6534

## 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: 3e-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_ratio: 0.15
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 0.7367        | 1.5748  | 200  | 0.2861          | 0.8443 |
| 0.1405        | 3.1496  | 400  | 0.2516          | 0.7550 |
| 0.061         | 4.7244  | 600  | 0.2315          | 0.7121 |
| 0.0295        | 6.2992  | 800  | 0.2600          | 0.6995 |
| 0.0161        | 7.8740  | 1000 | 0.2731          | 0.6721 |
| 0.0073        | 9.4488  | 1200 | 0.2925          | 0.6847 |
| 0.0033        | 11.0236 | 1400 | 0.3144          | 0.6692 |
| 0.0014        | 12.5984 | 1600 | 0.3111          | 0.6580 |
| 0.0002        | 14.1732 | 1800 | 0.3161          | 0.6557 |
| 0.0001        | 15.7480 | 2000 | 0.3197          | 0.6534 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1