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arampacha
/
whisper-large-uk-2

Automatic Speech Recognition
Transformers
PyTorch
Ukrainian
whisper
whisper-event
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
2
whisper-large-uk-2
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---
language:
- uk
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
- google/fleurs
model-index:
- name: whisper-large-uk
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: uk
      split: test
      args: uk
    metrics:
      - name: Wer
        type: wer
        value: 10.02262314404669
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Fleurs
      type: google/fleurs
      config: uk_ua
      split: test
      args: uk_ua
    metrics:
      - name: Wer
        type: wer
        value: 7.564370215727209
---

<!-- 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-large-uk

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2527
- eval_wer: 10.0226
- eval_runtime: 9610.7996
- eval_samples_per_second: 0.747
- eval_steps_per_second: 0.023
- epoch: 1.8
- step: 1098

## 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: 5e-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1500
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2