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---
language:
- sl
license: apache-2.0
base_model: openai/whisper-small
tags:
- asr-sl
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: sl-asr-model-primary-small
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 13.0
type: mozilla-foundation/common_voice_13_0
args: 'config: sl, split: test'
metrics:
- name: Wer
type: wer
value: 0.3198070374574347
---
<!-- 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. -->
# sl-asr-model-primary-small
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small).
It achieves the following results on the evaluation set:
- Loss: 0.3394
- Wer: 0.3198
## Model description
Slovenian-ASR-model-primary, 242M paramerters
## Intended uses & limitations
Automatic speech recognition for Slovenian
## Training and evaluation data
EWCH/data-preprocessed-commonvoice-sl-80s
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.001
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.3415 | 1.0 | 650 | 0.3394 | 0.3198 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1
- Datasets 2.17.1
- Tokenizers 0.15.2
|