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---
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
|