---
language:
- lv
license: apache-2.0
base_model: arturslogins/whisper-medium-lv
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- ta-dataset/training
metrics:
- wer
model-index:
- name: Whisper medium LV - Arturs Logins
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Recorded Voice
      type: ta-dataset/training
      config: lv
      split: test
      args: 'config: lv, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 43.705463182897866
---

<!-- 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 LV - Arturs Logins

This model is a fine-tuned version of [arturslogins/whisper-medium-lv](https://huggingface.co/arturslogins/whisper-medium-lv) on the Recorded Voice dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0843
- Wer: 43.7055

## 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: 12
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0097        | 6.3898  | 1000 | 0.9780          | 45.8432 |
| 0.0023        | 12.7796 | 2000 | 1.0158          | 44.9525 |
| 0.0002        | 19.1693 | 3000 | 1.0549          | 46.1758 |
| 0.0001        | 25.5591 | 4000 | 1.0765          | 44.9881 |
| 0.0001        | 31.9489 | 5000 | 1.0843          | 43.7055 |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.0.1
- Datasets 2.19.0
- Tokenizers 0.19.1