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---
language:
- hu
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- fsicoli/common_voice_18_0
metrics:
- wer
model-index:
- name: Whisper Small Hu CV18
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: google/flerus
type: f
config: hu_hu
split: train
args: hu_hu
metrics:
- name: Wer
type: wer
value: 25.98178929048856
pipeline_tag: automatic-speech-recognition
---
<!-- 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 Small Hu CV18
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the Common Voice 18.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6647
- Wer Ortho: 32.6950
- Wer: 25.9818
## 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: 2.5e-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 |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.2902 | 0.1723 | 250 | 0.6498 | 43.8115 | 38.8390 |
| 0.235 | 0.3446 | 500 | 0.6526 | 43.4572 | 37.5766 |
| 0.1898 | 0.5169 | 750 | 0.6127 | 40.0623 | 34.8072 |
| 0.177 | 0.6892 | 1000 | 0.5866 | 39.0613 | 33.7390 |
| 0.1461 | 0.8615 | 1250 | 0.5848 | 37.2397 | 31.7552 |
| 0.0834 | 1.0338 | 1500 | 0.5942 | 36.6963 | 30.8611 |
| 0.0783 | 1.2061 | 1750 | 0.5973 | 36.2904 | 29.8850 |
| 0.0757 | 1.3784 | 2000 | 0.6127 | 36.8602 | 30.0451 |
| 0.0737 | 1.5507 | 2250 | 0.5925 | 35.8202 | 29.6189 |
| 0.0724 | 1.7229 | 2500 | 0.5721 | 34.6654 | 29.0627 |
| 0.0707 | 1.8952 | 2750 | 0.5818 | 34.6326 | 28.4650 |
| 0.0292 | 2.0675 | 3000 | 0.5917 | 34.4423 | 28.0841 |
| 0.0288 | 2.2398 | 3250 | 0.6147 | 34.3465 | 28.0210 |
| 0.0283 | 2.4121 | 3500 | 0.6279 | 34.7310 | 28.1572 |
| 0.0319 | 2.5844 | 3750 | 0.6122 | 33.9229 | 27.3514 |
| 0.0292 | 2.7567 | 4000 | 0.5988 | 33.6947 | 27.7600 |
| 0.0262 | 2.9290 | 4250 | 0.6170 | 33.8876 | 27.3716 |
| 0.0093 | 3.1013 | 4500 | 0.6297 | 32.9862 | 26.4131 |
| 0.0094 | 3.2736 | 4750 | 0.6167 | 32.2336 | 26.3790 |
| 0.0086 | 3.4459 | 5000 | 0.6430 | 32.9068 | 26.3904 |
| 0.0094 | 3.6182 | 5250 | 0.6432 | 32.9749 | 26.4358 |
| 0.0088 | 3.7905 | 5500 | 0.6330 | 32.8438 | 26.3551 |
| 0.0082 | 3.9628 | 5750 | 0.6530 | 33.4325 | 26.6212 |
| 0.0035 | 4.1351 | 6000 | 0.6549 | 32.8589 | 26.1924 |
| 0.003 | 4.3074 | 6250 | 0.6625 | 32.7757 | 25.9175 |
| 0.003 | 4.4797 | 6500 | 0.6684 | 32.6950 | 25.8393 |
| 0.0032 | 4.6520 | 6750 | 0.6622 | 32.3912 | 25.7687 |
| 0.0027 | 4.8243 | 7000 | 0.6667 | 32.6585 | 25.8847 |
| 0.0028 | 4.9966 | 7250 | 0.6647 | 32.6950 | 25.9818 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.3.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1 |