---
language:
- pl
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
- google/fleurs
base_model: openai/whisper-small
model-index:
- name: Whisper Small PL
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0
      type: mozilla-foundation/common_voice_11_0
      config: pl
      split: test
    metrics:
    - type: wer
      value: 14.57
      name: WER
    - type: wer_without_norm
      value: 33.57
      name: WER unnormalized
    - type: cer
      value: 4.02
      name: CER
    - type: mer
      value: 14.37
      name: MER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: facebook/voxpopuli
      type: facebook/voxpopuli
      config: pl
      split: test
    metrics:
    - type: wer
      value: 15.73
      name: WER
    - type: wer_without_norm
      value: 34.51
      name: WER unnormalized
    - type: cer
      value: 7.73
      name: CER
    - type: mer
      value: 15.28
      name: MER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: google/fleurs
      type: google/fleurs
      config: pl_pl
      split: test
    metrics:
    - type: wer
      value: 16.79
      name: WER
    - type: wer_without_norm
      value: 35.69
      name: WER unnormalized
    - type: cer
      value: 4.99
      name: CER
    - type: mer
      value: 16.55
      name: MER
---

<!-- 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 PL

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 and the FLEURS datasets.
It achieves the following results on the evaluation set:
- eval_loss: 0.3571
- eval_wer: 14.8004
- eval_runtime: 2233.4204
- eval_samples_per_second: 3.714
- eval_steps_per_second: 0.232
- epoch: 4.03
- step: 3000

## 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: 24
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 8000
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2