---
base_model: openai/whisper-medium
datasets:
- Marcusxx/CHUNGNAM_Addresses_NO_NUM
language:
- ko
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
model-index:
- name: CHUNGNAM_FM_AddressesM_model
  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. -->

# CHUNGNAM_FM_AddressesM_model

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Marcusxx/CHUNGNAM_Addresses_NO_NUM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2603
- Cer: 6.2263

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 20000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Cer     |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|
| 0.1938        | 0.6906  | 1000  | 0.2020          | 5.9531  |
| 0.1554        | 1.3812  | 2000  | 0.1852          | 5.9452  |
| 0.1048        | 2.0718  | 3000  | 0.1793          | 5.8234  |
| 0.1126        | 2.7624  | 4000  | 0.1794          | 7.6374  |
| 0.0695        | 3.4530  | 5000  | 0.1922          | 6.2990  |
| 0.0382        | 4.1436  | 6000  | 0.1999          | 6.2872  |
| 0.0385        | 4.8343  | 7000  | 0.2019          | 7.5529  |
| 0.0203        | 5.5249  | 8000  | 0.2141          | 7.6944  |
| 0.0142        | 6.2155  | 9000  | 0.2211          | 6.0239  |
| 0.0129        | 6.9061  | 10000 | 0.2190          | 8.6417  |
| 0.0109        | 7.5967  | 11000 | 0.2262          | 8.0187  |
| 0.0062        | 8.2873  | 12000 | 0.2286          | 10.8626 |
| 0.0074        | 8.9779  | 13000 | 0.2323          | 7.1874  |
| 0.005         | 9.6685  | 14000 | 0.2370          | 7.7829  |
| 0.0046        | 10.3591 | 15000 | 0.2415          | 6.2243  |
| 0.0021        | 11.0497 | 16000 | 0.2459          | 6.0946  |
| 0.002         | 11.7403 | 17000 | 0.2474          | 6.1713  |
| 0.0009        | 12.4309 | 18000 | 0.2572          | 6.0887  |
| 0.0001        | 13.1215 | 19000 | 0.2582          | 6.2715  |
| 0.0002        | 13.8122 | 20000 | 0.2603          | 6.2263  |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.2.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1