---
language:
- sr
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- google/fleurs
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_rs
      split: test
      args: sr_rs
    metrics:
    - name: Wer
      type: wer
      value: 0.17942107976725344
---

<!-- 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 the Google Fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3577
- Wer Ortho: 0.2072
- Wer: 0.1794

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 4000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.0341        | 2.49  | 500  | 0.2704          | 0.2074    | 0.1789 |
| 0.0109        | 4.98  | 1000 | 0.3091          | 0.2075    | 0.1774 |
| 0.006         | 7.46  | 1500 | 0.3143          | 0.2031    | 0.1713 |
| 0.0081        | 9.95  | 2000 | 0.3284          | 0.2070    | 0.1754 |
| 0.0038        | 12.44 | 2500 | 0.3426          | 0.2099    | 0.1805 |
| 0.0042        | 14.93 | 3000 | 0.3630          | 0.2113    | 0.1821 |
| 0.0032        | 17.41 | 3500 | 0.3659          | 0.2089    | 0.1791 |
| 0.0046        | 19.9  | 4000 | 0.3577          | 0.2072    | 0.1794 |


### Framework versions

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