metadata
license: apache-2.0
base_model: openai/whisper-medium
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
language:
- hu
widget:
- example_title: Sample 1
src: >-
https://huggingface.co/datasets/Hungarians/samples/resolve/main/Sample1.flac
- example_title: Sample 2
src: >-
https://huggingface.co/datasets/Hungarians/samples/resolve/main/Sample2.flac
metrics:
- wer
pipeline_tag: automatic-speech-recognition
model-index:
- name: Whisper Medium Hungarian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 16.0 - Hungarian
type: mozilla-foundation/common_voice_16_0
config: hu
split: test
args: hu
metrics:
- name: Wer
type: wer
value: 5.55
verified: true
Whisper medium Hu
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0875
- Wer Ortho: 6.6934
- Wer: 5.5500
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: 6.25e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 500
- training_steps: 15000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Wer Ortho |
|---|---|---|---|---|---|
| 0.1877 | 0.33 | 1000 | 0.2104 | 17.8832 | 20.5799 |
| 0.136 | 0.67 | 2000 | 0.1561 | 13.4717 | 16.2140 |
| 0.1117 | 1.0 | 3000 | 0.1245 | 13.4198 | 10.9487 |
| 0.0673 | 1.34 | 4000 | 0.1148 | 12.0107 | 9.7836 |
| 0.0657 | 1.67 | 5000 | 0.1006 | 10.3547 | 8.4702 |
| 0.0264 | 2.01 | 6000 | 0.0905 | 9.0931 | 7.2250 |
| 0.0284 | 2.34 | 7000 | 0.0916 | 8.7137 | 7.2221 |
| 0.0311 | 2.68 | 8000 | 0.0879 | 8.0242 | 6.6914 |
| 0.0177 | 3.01 | 9000 | 0.0841 | 7.6960 | 6.3860 |
| 0.0177 | 3.35 | 10000 | 0.0844 | 7.2173 | 6.0125 |
| 0.0126 | 3.68 | 11000 | 0.0848 | 7.2052 | 5.9739 |
| 0.0078 | 4.02 | 12000 | 0.0865 | 7.1179 | 6.0629 |
| 0.0113 | 4.35 | 13000 | 0.0863 | 6.9312 | 5.7990 |
| 0.0115 | 4.69 | 14000 | 0.0853 | 7.0185 | 5.8968 |
| 0.0071 | 5.02 | 15000 | 0.0875 | 6.6934 | 5.5500 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0