metadata
language:
- hi
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Small Korean
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_16_1 hi
type: mozilla-foundation/common_voice_16_1
config: hi
split: test
args: hi
metrics:
- name: Wer
type: wer
value: 26.295720650709768
Whisper Small Korean
This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common_voice_16_1 hi dataset. It achieves the following results on the evaluation set:
- Loss: 0.4670
- Wer: 26.2957
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: 12
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2366 | 2.04 | 1000 | 0.4182 | 27.3008 |
| 0.0693 | 4.08 | 2000 | 0.4670 | 26.2957 |
| 0.0252 | 7.03 | 3000 | 0.5334 | 26.9174 |
| 0.0052 | 9.07 | 4000 | 0.6184 | 26.7869 |
| 0.0029 | 12.03 | 5000 | 0.6465 | 26.6853 |
Framework versions
- Transformers 4.39.0
- Pytorch 2.2.1+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2