---
library_name: transformers
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mangoo111/eval
model-index:
- name: test_whisper
  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. -->

# test_whisper

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mangoo111/eval dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0539
- Cer: 2.2521

## 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: 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 0.0266        | 2.8818  | 1000 | 0.0650          | 2.6964 |
| 0.0019        | 5.7637  | 2000 | 0.0551          | 2.1164 |
| 0.0011        | 8.6455  | 3000 | 0.0539          | 2.2336 |
| 0.0008        | 11.5274 | 4000 | 0.0539          | 2.2521 |


### Framework versions

- Transformers 4.49.0.dev0
- Pytorch 2.3.0a0+6ddf5cf85e.nv24.04
- Datasets 2.17.1
- Tokenizers 0.21.0