---
language:
- ml
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- thennal/imasc
metrics:
- wer
model-index:
- name: Whisper Small Ml - IMaSC
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: ICFOSS Malayalam Speech Corpus
      type: thennal/imasc
      config: ml
      split: test
      args: ml
    metrics:
    - name: Wer
      type: wer
      value: 75.40229885057471
---

<!-- 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 Ml - IMaSC

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the ICFOSS Malayalam Speech Corpus dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2750
- Wer: 75.4023
- Cer: 20.0050

## 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: 64
- eval_batch_size: 32
- 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: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.0678        | 0.93  | 500  | 0.2756          | 86.6667 | 31.1467 |
| 0.0342        | 1.86  | 1000 | 0.2424          | 73.7931 | 20.3305 |
| 0.0192        | 2.78  | 1500 | 0.2615          | 74.7126 | 19.8297 |
| 0.0107        | 3.71  | 2000 | 0.2750          | 75.4023 | 20.0050 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2