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---
license: apache-2.0
base_model: openai/whisper-tiny
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 Tiny Hu 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: 15.7367
verified: true
---
<!-- 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 Tiny Hu v2
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 16.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1930
- Wer Ortho: 17.3040
- Wer: 15.7367
## 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: 4e-05
- 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 Ortho | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:-------:|
| 0.5487 | 0.33 | 1000 | 0.5970 | 55.5492 | 52.2206 |
| 0.3922 | 0.67 | 2000 | 0.4419 | 43.1109 | 39.9911 |
| 0.3242 | 1.0 | 3000 | 0.3662 | 37.2727 | 34.2040 |
| 0.2517 | 1.34 | 4000 | 0.3329 | 33.7890 | 30.8746 |
| 0.2455 | 1.67 | 5000 | 0.2925 | 30.6185 | 28.0196 |
| 0.1398 | 2.01 | 6000 | 0.2600 | 27.1709 | 24.5983 |
| 0.1421 | 2.34 | 7000 | 0.2491 | 26.1291 | 23.6347 |
| 0.1578 | 2.68 | 8000 | 0.2342 | 24.4761 | 22.0783 |
| 0.0732 | 3.01 | 9000 | 0.2163 | 22.1245 | 19.8547 |
| 0.0941 | 3.35 | 10000 | 0.2143 | 22.2058 | 19.8399 |
| 0.0936 | 3.68 | 11000 | 0.2094 | 20.5980 | 18.7756 |
| 0.0489 | 4.02 | 12000 | 0.2027 | 18.9630 | 17.2665 |
| 0.0548 | 4.35 | 13000 | 0.1981 | 18.4933 | 16.5491 |
| 0.0585 | 4.69 | 14000 | 0.1953 | 17.7195 | 15.7693 |
| 0.0356 | 5.02 | 15000 | 0.1930 | 17.3040 | 15.7367 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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