---
language:
- hi
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- aihub_adult_speed
model-index:
- name: whisper-small-ko-Yspeed2
  results: []
---

<!-- 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-ko-Yspeed2

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the aihub adult speed changed dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2744
- Cer: 10.9845

## 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: 8
- 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: 50
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4529        | 0.13  | 100  | 0.3102          | 7.5952  |
| 0.2772        | 0.26  | 200  | 0.2821          | 9.2164  |
| 0.2264        | 0.39  | 300  | 0.2872          | 8.2942  |
| 0.2172        | 0.52  | 400  | 0.2665          | 7.7185  |
| 0.1956        | 0.64  | 500  | 0.2784          | 10.5263 |
| 0.17          | 0.77  | 600  | 0.2786          | 9.4866  |
| 0.1787        | 0.9   | 700  | 0.2761          | 11.3017 |
| 0.0818        | 1.03  | 800  | 0.2732          | 10.0270 |
| 0.0616        | 1.16  | 900  | 0.2732          | 9.1753  |
| 0.0721        | 1.29  | 1000 | 0.2763          | 10.6732 |
| 0.0661        | 1.42  | 1100 | 0.2798          | 15.2432 |
| 0.0768        | 1.55  | 1200 | 0.2730          | 13.8393 |
| 0.0602        | 1.68  | 1300 | 0.2714          | 11.5484 |
| 0.0667        | 1.81  | 1400 | 0.2730          | 13.0933 |
| 0.0675        | 1.93  | 1500 | 0.2744          | 10.9845 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0