---
language:
- hi
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- konnakol
metrics:
- wer
model-index:
- name: Whisper Small Hi - Gopika Krishnan
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Konnakol
      type: konnakol
      args: 'config: hi, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 87.64568764568764
---

<!-- 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 Hi - Gopika Krishnan

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Konnakol dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2352
- Wer: 87.6457

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 16
- 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss | Wer     |
|:-------------:|:--------:|:----:|:---------------:|:-------:|
| 0.1507        | 21.7391  | 500  | 1.2891          | 87.7622 |
| 0.0428        | 43.4783  | 1000 | 1.4133          | 93.7063 |
| 0.0111        | 65.2174  | 1500 | 1.7252          | 89.3939 |
| 0.0063        | 86.9565  | 2000 | 1.8134          | 85.8974 |
| 0.0035        | 108.6957 | 2500 | 2.0195          | 85.7809 |
| 0.003         | 130.4348 | 3000 | 2.0771          | 87.8788 |
| 0.0027        | 152.1739 | 3500 | 2.1378          | 87.5291 |
| 0.0025        | 173.9130 | 4000 | 2.1730          | 86.4802 |
| 0.0025        | 195.6522 | 4500 | 2.2126          | 87.8788 |
| 0.0025        | 217.3913 | 5000 | 2.2352          | 87.6457 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1