---
language:
- ml
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- thennal/imasc
metrics:
- wer
model-index:
- name: Whisper Large V2 Malayalam
  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: 44.13793103448276
---

<!-- 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 Large V2 Malayalam

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the ICFOSS Malayalam Speech Corpus dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0617
- Wer: 44.1379
- Cer: 9.6895

## 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: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.1071        | 0.13  | 500  | 0.1274          | 62.9885 | 15.0225 |
| 0.0693        | 0.26  | 1000 | 0.1052          | 57.4713 | 13.0696 |
| 0.054         | 0.39  | 1500 | 0.0902          | 48.0460 | 11.5173 |
| 0.0494        | 0.51  | 2000 | 0.0774          | 46.4368 | 10.7912 |
| 0.0446        | 0.64  | 2500 | 0.0722          | 46.8966 | 10.7161 |
| 0.0463        | 0.77  | 3000 | 0.0699          | 46.2069 | 10.3405 |
| 0.0347        | 0.9   | 3500 | 0.0662          | 43.6782 | 10.2404 |
| 0.0233        | 1.03  | 4000 | 0.0688          | 45.7471 | 10.4407 |
| 0.0226        | 1.16  | 4500 | 0.0642          | 44.5977 | 10.1152 |
| 0.0194        | 1.28  | 5000 | 0.0617          | 44.1379 | 9.6895  |


### Framework versions

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