transformers tensorboard safetensors whisper automatic-speech-recognition asr-sl generated_from_trainer sl dataset:mozilla-foundation/common_voice_13_0 base_model:openai/whisper-medium license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- sl
license: apache-2.0
base_model: openai/whisper-medium
tags:
- asr-sl
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: sl-asr-model-primary-medium
  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: 0.19551645856980704
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# sl-asr-model-primary-medium

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium).
It achieves the following results on the evaluation set:
- Loss: 0.2198
- Wer: 0.1955

## Model description

Slovenian-ASR-model-primary, 754M paramerters

## Intended uses & limitations

Automatic speech recognition for Slovenia

## Training and evaluation data

EWCH/data-preprocessed-commonvoice-sl-80m

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.1909        | 1.0   | 650  | 0.2198          | 0.1955 |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.2.1
- Datasets 2.17.1
- Tokenizers 0.15.2
