---
language:
- sr
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- google/fleurs
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Medium Sr Fleurs
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Google Fleurs
      type: google/fleurs
      config: sr
      split: test
      args: sr
    metrics:
    - name: Wer
      type: wer
      value: 0.07884448305821025
---

<!-- 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 Medium Sr Fleurs

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on combined Google Fleurs and Mozilla Common Volice 13 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1947
- Wer Ortho: 0.1874
- Wer: 0.0788

## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 1500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.072         | 1.34  | 500  | 0.1769          | 0.1896    | 0.0912 |
| 0.0223        | 2.67  | 1000 | 0.1774          | 0.1993    | 0.0832 |
| 0.0101        | 4.01  | 1500 | 0.1947          | 0.1874    | 0.0788 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3