metadata
language:
- hu
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Tiny Hu CV17
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: common_voice_11_0
config: hu
split: None
args: hu
metrics:
- name: Wer
type: wer
value: 9.925882004150607
Whisper Tiny Hu CV17
This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1387
- Wer Ortho: 10.7883
- Wer: 9.9259
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: 7.5e-05
- train_batch_size: 64
- eval_batch_size: 32
- 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 Ortho | Wer |
|---|---|---|---|---|---|
| 0.6432 | 0.3298 | 250 | 0.7031 | 59.9211 | 57.3051 |
| 0.4839 | 0.6596 | 500 | 0.5256 | 50.4185 | 47.3406 |
| 0.4127 | 0.9894 | 750 | 0.4089 | 40.9250 | 37.8002 |
| 0.2858 | 1.3193 | 1000 | 0.3434 | 34.4725 | 31.8885 |
| 0.2616 | 1.6491 | 1250 | 0.3027 | 32.2956 | 29.2203 |
| 0.2448 | 1.9789 | 1500 | 0.2571 | 28.1705 | 25.3780 |
| 0.1474 | 2.3087 | 1750 | 0.2318 | 25.4426 | 22.8343 |
| 0.1434 | 2.6385 | 2000 | 0.2112 | 22.7749 | 20.3647 |
| 0.14 | 2.9683 | 2250 | 0.1922 | 20.1102 | 17.7883 |
| 0.0768 | 3.2982 | 2500 | 0.1797 | 18.2344 | 15.9917 |
| 0.0764 | 3.6280 | 2750 | 0.1678 | 16.5573 | 14.6161 |
| 0.0737 | 3.9578 | 3000 | 0.1573 | 15.0337 | 13.6199 |
| 0.0375 | 4.2876 | 3250 | 0.1538 | 14.0130 | 12.3243 |
| 0.0357 | 4.6174 | 3500 | 0.1495 | 13.1970 | 11.7106 |
| 0.033 | 4.9472 | 3750 | 0.1435 | 11.9234 | 10.8005 |
| 0.0138 | 5.2770 | 4000 | 0.1422 | 11.8873 | 10.7026 |
| 0.0137 | 5.6069 | 4250 | 0.1398 | 11.4477 | 10.4684 |
| 0.0135 | 5.9367 | 4500 | 0.1381 | 11.1436 | 10.2639 |
| 0.0072 | 6.2665 | 4750 | 0.1388 | 10.7853 | 9.9140 |
| 0.0065 | 6.5963 | 5000 | 0.1387 | 10.7883 | 9.9259 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1