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---
language:
- hu
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: Whisper Tiny Hu CV18
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 18.0
type: fleurs
config: hu_hu
split: None
args: hu_hu
metrics:
- name: Wer
type: wer
value: 46.19517239639821
---
<!-- 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 CV18
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co./openai/whisper-tiny) on the Common Voice 18.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2308
- Wer Ortho: 51.3968
- Wer: 46.1952
## 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
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.5967 | 0.1723 | 250 | 1.2539 | 69.9246 | 66.9344 |
| 0.4456 | 0.3446 | 500 | 1.2200 | 65.5249 | 61.7108 |
| 0.3713 | 0.5169 | 750 | 1.1422 | 61.8665 | 58.0019 |
| 0.3337 | 0.6892 | 1000 | 1.1139 | 60.4332 | 55.7999 |
| 0.2829 | 0.8615 | 1250 | 1.1074 | 59.6528 | 56.2502 |
| 0.1931 | 1.0338 | 1500 | 1.1087 | 58.2686 | 53.8969 |
| 0.1855 | 1.2061 | 1750 | 1.1643 | 57.5828 | 52.8577 |
| 0.1827 | 1.3784 | 2000 | 1.1136 | 58.2951 | 54.2260 |
| 0.177 | 1.5507 | 2250 | 1.1326 | 57.4353 | 52.1628 |
| 0.1686 | 1.7229 | 2500 | 1.0970 | 54.8396 | 49.9067 |
| 0.1654 | 1.8952 | 2750 | 1.0957 | 56.3953 | 51.6975 |
| 0.0886 | 2.0675 | 3000 | 1.1150 | 53.5349 | 48.7805 |
| 0.0966 | 2.2398 | 3250 | 1.1417 | 54.4060 | 49.0113 |
| 0.0921 | 2.4121 | 3500 | 1.1387 | 53.9975 | 48.6001 |
| 0.0968 | 2.5844 | 3750 | 1.1587 | 53.8147 | 49.2660 |
| 0.0968 | 2.7567 | 4000 | 1.1459 | 52.8176 | 48.4438 |
| 0.086 | 2.9290 | 4250 | 1.1298 | 52.4784 | 47.4702 |
| 0.0456 | 3.1013 | 4500 | 1.1714 | 52.6663 | 47.3920 |
| 0.0487 | 3.2736 | 4750 | 1.1730 | 52.9524 | 48.1499 |
| 0.0475 | 3.4459 | 5000 | 1.1945 | 52.7898 | 47.3668 |
| 0.0442 | 3.6182 | 5250 | 1.2042 | 52.3410 | 47.3037 |
| 0.0434 | 3.7905 | 5500 | 1.1851 | 53.0205 | 47.7262 |
| 0.0438 | 3.9628 | 5750 | 1.1912 | 52.5869 | 48.0541 |
| 0.0211 | 4.1351 | 6000 | 1.2191 | 52.3562 | 47.9923 |
| 0.0198 | 4.3074 | 6250 | 1.2203 | 51.6136 | 46.6290 |
| 0.0185 | 4.4797 | 6500 | 1.2287 | 52.0297 | 46.4537 |
| 0.0196 | 4.6520 | 6750 | 1.2363 | 51.7183 | 46.2696 |
| 0.0196 | 4.8243 | 7000 | 1.2320 | 51.5594 | 46.0817 |
| 0.0178 | 4.9966 | 7250 | 1.2308 | 51.3968 | 46.1952 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.3.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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