---
library_name: transformers
language:
- hi
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- aihub_adult_baseline
model-index:
- name: whisper-small-ko-baseline
  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-baseline

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: 0.2914
- Cer: 8.5820

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.2433        | 0.1289 | 100  | 0.2943          | 7.8712  |
| 0.1379        | 0.2579 | 200  | 0.2758          | 7.4248  |
| 0.1105        | 0.3868 | 300  | 0.2831          | 7.6010  |
| 0.1231        | 0.5158 | 400  | 0.2671          | 7.2192  |
| 0.0984        | 0.6447 | 500  | 0.2721          | 7.2603  |
| 0.0938        | 0.7737 | 600  | 0.2742          | 7.1840  |
| 0.0954        | 0.9026 | 700  | 0.2718          | 6.9901  |
| 0.0385        | 1.0316 | 800  | 0.2649          | 6.9549  |
| 0.0302        | 1.1605 | 900  | 0.2645          | 7.5129  |
| 0.0388        | 1.2895 | 1000 | 0.2722          | 7.0606  |
| 0.0338        | 1.4184 | 1100 | 0.2819          | 7.8889  |
| 0.0389        | 1.5474 | 1200 | 0.2725          | 7.7479  |
| 0.0335        | 1.6763 | 1300 | 0.2716          | 8.3647  |
| 0.0331        | 1.8053 | 1400 | 0.2751          | 7.6774  |
| 0.0343        | 1.9342 | 1500 | 0.2825          | 7.8008  |
| 0.0134        | 2.0632 | 1600 | 0.2739          | 6.9079  |
| 0.0127        | 2.1921 | 1700 | 0.2779          | 8.8287  |
| 0.0141        | 2.3211 | 1800 | 0.2822          | 7.1429  |
| 0.0113        | 2.4500 | 1900 | 0.2864          | 8.6407  |
| 0.0131        | 2.5790 | 2000 | 0.2797          | 10.5909 |
| 0.0103        | 2.7079 | 2100 | 0.2835          | 8.4880  |
| 0.0117        | 2.8369 | 2200 | 0.2828          | 11.5425 |
| 0.0116        | 2.9658 | 2300 | 0.2832          | 9.5747  |
| 0.0046        | 3.0948 | 2400 | 0.2862          | 8.8640  |
| 0.0045        | 3.2237 | 2500 | 0.2877          | 10.0388 |
| 0.0061        | 3.3527 | 2600 | 0.2886          | 8.9991  |
| 0.0055        | 3.4816 | 2700 | 0.2894          | 8.4704  |
| 0.0052        | 3.6106 | 2800 | 0.2904          | 8.4410  |
| 0.0059        | 3.7395 | 2900 | 0.2908          | 10.3266 |
| 0.0051        | 3.8685 | 3000 | 0.2913          | 9.3280  |
| 0.0047        | 3.9974 | 3100 | 0.2914          | 8.5820  |


### Framework versions

- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0