metadata
license: apache-2.0
base_model: openai/whisper-small
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 Small Hungarian V2
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: 8.1
verified: true
Whisper Small Hu v2
This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set (at step 12000 best WER&CER modell):
- Loss: 0.1098
- Wer Ortho: 9.3671
- Wer: 8.1026
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: 1.25e-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: 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 Ortho | Wer |
---|---|---|---|---|---|
0.2871 | 0.33 | 1000 | 0.3110 | 31.4525 | 28.3160 |
0.1967 | 0.67 | 2000 | 0.2263 | 23.7836 | 20.9280 |
0.1542 | 1.0 | 3000 | 0.1808 | 19.5351 | 16.7032 |
0.1083 | 1.34 | 4000 | 0.1658 | 17.2709 | 14.8236 |
0.1054 | 1.67 | 5000 | 0.1438 | 14.9554 | 12.6653 |
0.0468 | 2.01 | 6000 | 0.1248 | 12.8869 | 10.8034 |
0.0437 | 2.34 | 7000 | 0.1235 | 12.2817 | 10.3913 |
0.05 | 2.68 | 8000 | 0.1197 | 11.4958 | 9.6887 |
0.022 | 3.01 | 9000 | 0.1119 | 10.4932 | 8.9623 |
0.0286 | 3.35 | 10000 | 0.1141 | 10.4149 | 9.0780 |
0.0233 | 3.68 | 11000 | 0.1150 | 10.0536 | 8.6837 |
0.0124 | 4.02 | 12000 | 0.1098 | 9.3671 | 8.1026 |
0.0165 | 4.35 | 13000 | 0.1143 | 9.7947 | 8.3813 |
0.0174 | 4.69 | 14000 | 0.1136 | 9.3249 | 8.0729 |
0.0107 | 5.02 | 15000 | 0.1150 | 9.2527 | 8.2745 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0