---
language:
- sr
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- espnet/yodas
metrics:
- wer
model-index:
- name: Whisper Small Yodas
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Yodas
      type: espnet/yodas
      config: sr
      split: test
      args: sr
    metrics:
    - name: Wer
      type: wer
      value: 0.11913993655269652
---

<!-- 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 Yodas

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Yodas dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1748
- Wer Ortho: 0.2143
- Wer: 0.1191

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.7316        | 0.24  | 500  | 0.2554          | 0.2942    | 0.2184 |
| 0.6996        | 0.49  | 1000 | 0.2136          | 0.2535    | 0.1563 |
| 0.6073        | 0.73  | 1500 | 0.1979          | 0.2374    | 0.1452 |
| 0.6032        | 0.98  | 2000 | 0.1872          | 0.2228    | 0.1280 |
| 0.4603        | 1.22  | 2500 | 0.1811          | 0.2136    | 0.1218 |
| 0.4142        | 1.46  | 3000 | 0.1767          | 0.2152    | 0.1200 |
| 0.4457        | 1.71  | 3500 | 0.1759          | 0.2159    | 0.1234 |
| 0.4376        | 1.95  | 4000 | 0.1748          | 0.2143    | 0.1191 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.1