---
base_model: openai/whisper-large
datasets:
- Marcusxx/cheonanAddresses
language:
- ko
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
model-index:
- name: cheonanAddresses_torch_large_model_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. -->

# cheonanAddresses_torch_large_model_model

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the Marcusxx/cheonanAddresses dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0534
- Cer: 1.8909

## 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Cer    |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 0.0757        | 0.3101 | 1000  | 0.0772          | 2.2598 |
| 0.0714        | 0.6202 | 2000  | 0.0720          | 2.3372 |
| 0.0624        | 0.9302 | 3000  | 0.0676          | 2.2765 |
| 0.0583        | 1.2403 | 4000  | 0.0642          | 2.2266 |
| 0.0611        | 1.5504 | 5000  | 0.0604          | 2.0681 |
| 0.0552        | 1.8605 | 6000  | 0.0590          | 2.1282 |
| 0.0497        | 2.1705 | 7000  | 0.0569          | 2.0233 |
| 0.0423        | 2.4806 | 8000  | 0.0560          | 1.9835 |
| 0.0495        | 2.7907 | 9000  | 0.0538          | 1.9387 |
| 0.0364        | 3.1008 | 10000 | 0.0534          | 1.8909 |


### Framework versions

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