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---
language:
- hu
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Hungarian - Robust
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0 hu
type: mozilla-foundation/common_voice_11_0
config: hu
split: test
args: hu
metrics:
- type: wer
value: 30.904239549362583
name: Wer
- type: wer
value: 26.15
name: WER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: google/fleurs
type: google/fleurs
config: hu_hu
split: test
metrics:
- type: wer
value: 35.49
name: WER
---
<!-- 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 Hungarian - Robust
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 hu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5243
- Wer: 30.9042
## 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: 128
- eval_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0763 | 7.46 | 500 | 0.5268 | 40.5099 |
| 0.0147 | 14.93 | 1000 | 0.5233 | 36.1429 |
| 0.0064 | 22.39 | 1500 | 0.5467 | 35.0934 |
| 0.0045 | 29.85 | 2000 | 0.5434 | 34.2929 |
| 0.0019 | 37.31 | 2500 | 0.5348 | 32.7868 |
| 0.0008 | 44.78 | 3000 | 0.5314 | 32.0605 |
| 0.0008 | 52.24 | 3500 | 0.5438 | 32.6920 |
| 0.0005 | 59.7 | 4000 | 0.5428 | 32.0931 |
| 0.0003 | 67.16 | 4500 | 0.5328 | 31.2511 |
| 0.0004 | 74.63 | 5000 | 0.5292 | 31.1236 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|