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---
language:
- kr
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
datasets:
- Jungwonchang/ksponspeech
metrics:
- wer
model-index:
- name: Whisper large-v2, KsponSpeech
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: KsponSpeech
type: Jungwonchang/ksponspeech
config: dev
split: validation
args: dev
metrics:
- name: Wer
type: wer
value: 42.225687000584685
---
<!-- 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 large-v2, KsponSpeech
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the KsponSpeech dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2946
- Wer: 42.2257
## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 2000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3315 | 0.25 | 500 | 0.3446 | 41.5319 |
| 0.3204 | 0.5 | 1000 | 0.3229 | 37.7003 |
| 0.2967 | 0.75 | 1500 | 0.3054 | 38.3980 |
| 0.2859 | 1.0 | 2000 | 0.2946 | 42.2257 |
### Framework versions
- Transformers 4.31.0
- Pytorch 1.12.1+cu116
- Datasets 2.14.0
- Tokenizers 0.12.1
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