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---
language:
- hu
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Base 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: 8.132226504595316
---
<!-- 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 Base Hu CV17
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1148
- Wer Ortho: 8.9576
- Wer: 8.1322
## 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: 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 |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.5156 | 0.3298 | 250 | 0.5620 | 52.2010 | 49.0898 |
| 0.3906 | 0.6596 | 500 | 0.4262 | 43.7131 | 40.2668 |
| 0.3276 | 0.9894 | 750 | 0.3243 | 33.3915 | 30.2728 |
| 0.2161 | 1.3193 | 1000 | 0.2639 | 27.8152 | 24.9778 |
| 0.2009 | 1.6491 | 1250 | 0.2314 | 24.8705 | 21.9923 |
| 0.1835 | 1.9789 | 1500 | 0.1938 | 21.4922 | 18.8260 |
| 0.0973 | 2.3087 | 1750 | 0.1748 | 18.8396 | 16.0243 |
| 0.0963 | 2.6385 | 2000 | 0.1600 | 17.0240 | 14.8651 |
| 0.0913 | 2.9683 | 2250 | 0.1414 | 14.0853 | 12.1198 |
| 0.046 | 3.2982 | 2500 | 0.1374 | 13.2000 | 11.4468 |
| 0.0447 | 3.6280 | 2750 | 0.1306 | 12.5677 | 10.9191 |
| 0.0409 | 3.9578 | 3000 | 0.1216 | 11.1436 | 9.8251 |
| 0.0173 | 4.2876 | 3250 | 0.1205 | 10.4812 | 9.2292 |
| 0.0165 | 4.6174 | 3500 | 0.1180 | 10.2343 | 9.0898 |
| 0.0152 | 4.9472 | 3750 | 0.1149 | 9.6200 | 8.5562 |
| 0.0061 | 5.2770 | 4000 | 0.1149 | 9.1021 | 8.1589 |
| 0.0056 | 5.6069 | 4250 | 0.1144 | 9.2406 | 8.2864 |
| 0.006 | 5.9367 | 4500 | 0.1138 | 9.0630 | 8.1559 |
| 0.0036 | 6.2665 | 4750 | 0.1148 | 9.0148 | 8.1737 |
| 0.0033 | 6.5963 | 5000 | 0.1148 | 8.9576 | 8.1322 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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