---
language:
- hi
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
model-index:
- name: Whisper Small ko-Yfreq - syp1229
  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-Yfreq - syp1229

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the aihub Y dialogue dataset.
It achieves the following results on the evaluation set:
- Loss: 4.5884
- Cer: 0.8501

## 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: 0.002
- train_batch_size: 16
- 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: 100
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.7567        | 0.3   | 100  | 6.1420          | 0.9849 |
| 5.5645        | 0.59  | 200  | 5.7215          | 0.9903 |
| 5.1849        | 0.89  | 300  | 5.3951          | 0.9170 |
| 5.0416        | 1.18  | 400  | 5.3100          | 0.8497 |
| 4.5767        | 1.48  | 500  | 5.0656          | 0.9404 |
| 4.6818        | 1.78  | 600  | 5.0057          | 0.8237 |
| 4.4227        | 2.07  | 700  | 4.9162          | 0.8776 |
| 4.3057        | 2.37  | 800  | 4.8226          | 0.8212 |
| 4.3631        | 2.66  | 900  | 4.7700          | 0.8636 |
| 4.1999        | 2.96  | 1000 | 4.6969          | 0.8476 |
| 4.0789        | 3.25  | 1100 | 4.7653          | 0.9222 |
| 4.1997        | 3.55  | 1200 | 4.6345          | 0.8642 |
| 3.8299        | 3.85  | 1300 | 4.6444          | 0.8282 |
| 3.6904        | 4.14  | 1400 | 4.6633          | 0.8451 |
| 3.7531        | 4.44  | 1500 | 4.6527          | 0.9382 |
| 3.8045        | 4.73  | 1600 | 4.5884          | 0.8501 |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3