---
library_name: transformers
language:
- lv
license: apache-2.0
base_model: openai/whisper-medium
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper medium LV - Felikss Kleins
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0
      type: mozilla-foundation/common_voice_17_0
      config: lv
      split: None
      args: 'config: lv, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 13.506122934252765
---

<!-- 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 - Felikss Kleins

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1848
- Wer: 13.5061

## 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: 6
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 12
- 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| No log        | 0.04   | 200  | 0.8471          | 30.5453 |
| 1.8421        | 0.08   | 400  | 0.3571          | 27.1906 |
| 0.5851        | 0.12   | 600  | 0.3146          | 23.9508 |
| 0.4787        | 0.16   | 800  | 0.2913          | 23.2454 |
| 0.4845        | 0.2    | 1000 | 0.2736          | 20.9388 |
| 0.4845        | 0.24   | 1200 | 0.2495          | 19.1951 |
| 0.4004        | 0.28   | 1400 | 0.2416          | 18.4600 |
| 0.357         | 1.018  | 1600 | 0.2300          | 17.8576 |
| 0.3381        | 1.058  | 1800 | 0.2261          | 17.1125 |
| 0.3052        | 1.098  | 2000 | 0.2151          | 16.6013 |
| 0.3052        | 1.138  | 2200 | 0.2154          | 16.1673 |
| 0.2636        | 1.178  | 2400 | 0.2256          | 17.3107 |
| 0.2805        | 1.218  | 2600 | 0.2059          | 15.6482 |
| 0.2331        | 1.258  | 2800 | 0.2022          | 15.4599 |
| 0.2245        | 1.298  | 3000 | 0.1971          | 15.0953 |
| 0.2245        | 2.036  | 3200 | 0.1988          | 14.7604 |
| 0.2312        | 2.076  | 3400 | 0.1941          | 14.5623 |
| 0.2077        | 2.116  | 3600 | 0.1915          | 14.2175 |
| 0.1923        | 2.156  | 3800 | 0.1935          | 14.4018 |
| 0.2012        | 2.196  | 4000 | 0.1906          | 14.4850 |
| 0.2012        | 2.2360 | 4200 | 0.1880          | 13.9302 |
| 0.1694        | 2.276  | 4400 | 0.1860          | 14.1640 |
| 0.1548        | 3.014  | 4600 | 0.1855          | 13.6508 |
| 0.1628        | 3.054  | 4800 | 0.1850          | 13.5557 |
| 0.1529        | 3.094  | 5000 | 0.1848          | 13.5061 |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.0.1
- Datasets 3.0.0
- Tokenizers 0.19.1