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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 Small 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: 5.627038
---
<!-- 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 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: 0.0862
- Wer Ortho: 6.536794
- Wer: 5.627038
## 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
- training_steps: 6000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.3208 | 0.3298 | 250 | 0.3558 | 34.5839 | 31.0969 |
| 0.2542 | 0.6596 | 500 | 0.2683 | 27.2010 | 24.2218 |
| 0.2204 | 0.9894 | 750 | 0.2035 | 22.2962 | 19.4960 |
| 0.1301 | 1.3193 | 1000 | 0.1673 | 17.6683 | 15.2446 |
| 0.1171 | 1.6491 | 1250 | 0.1433 | 15.2445 | 12.9677 |
| 0.1075 | 1.9789 | 1500 | 0.1192 | 12.8658 | 10.7827 |
| 0.0492 | 2.3087 | 1750 | 0.1091 | 11.2489 | 9.1877 |
| 0.0491 | 2.6385 | 2000 | 0.1046 | 10.7582 | 9.0543 |
| 0.0472 | 2.9683 | 2250 | 0.0945 | 9.0750 | 7.5037 |
| 0.0203 | 3.2982 | 2500 | 0.0932 | 8.5873 | 7.2428 |
| 0.0188 | 3.6280 | 2750 | 0.0900 | 8.2019 | 6.9671 |
| 0.0183 | 3.9578 | 3000 | 0.0859 | 7.5154 | 6.4008 |
| 0.0068 | 4.2876 | 3250 | 0.0837 | 7.2052 | 6.1785 |
| 0.0064 | 4.6174 | 3500 | 0.0843 | 6.9613 | 6.0213 |
| 0.0061 | 4.9472 | 3750 | 0.0847 | 6.9674 | 5.9383 |
| 0.0025 | 5.2770 | 4000 | 0.0851 | 6.6994 | 5.7723 |
| 0.0023 | 5.6069 | 4250 | 0.0847 | 6.6331 | 5.6863 |
| 0.0022 | 5.9367 | 4500 | 0.0844 | 6.6211 | 5.7338 |
| 0.0014 | 6.2665 | 4750 | 0.0855 | 6.5789 | 5.6834 |
| 0.0011 | 6.5963 | 5000 | 0.0856 | 6.5609 | 5.6567 |
| 0.0012 | 6.9261 | 5250 | 0.0862 | 6.5368 | 5.6270 |
| 0.0009 | 7.2559 | 5500 | 0.0870 | 6.5699 | 5.6597 |
| 0.0009 | 7.5858 | 5750 | 0.0873 | 6.5639 | 5.6597 |
| 0.001 | 7.9156 | 6000 | 0.0873 | 6.5518 | 5.6389 |
### Framework versions
- Transformers 4.41.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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