---
language:
- lt
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: whisper-lt-finetune
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: 'null'
      split: None
      args: 'config: lt, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 28.115930505307517
---

<!-- 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-lt-finetune

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3634
- Wer: 28.1159

## 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-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: 250
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.399         | 0.9   | 500  | 0.4877          | 49.1790 |
| 0.1925        | 1.8   | 1000 | 0.4019          | 39.1325 |
| 0.0734        | 2.7   | 1500 | 0.3989          | 37.5581 |
| 0.0324        | 3.6   | 2000 | 0.3947          | 32.9662 |
| 0.0053        | 5.4   | 3000 | 0.3708          | 29.2808 |
| 0.0007        | 7.19  | 4000 | 0.3634          | 28.1159 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2