---
library_name: transformers
language:
- lv
license: apache-2.0
base_model: FelixK7/whisper-medium-lv-ver2
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_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 16.0
      type: mozilla-foundation/common_voice_16_0
      config: lv
      split: None
      args: 'config: lv, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 19.39252336448598
---

<!-- 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 [FelixK7/whisper-medium-lv-ver2](https://huggingface.co/FelixK7/whisper-medium-lv-ver2) on the Common Voice 16.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2882
- Wer: 19.3925

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss | Wer     |
|:-------------:|:--------:|:----:|:---------------:|:-------:|
| No log        | 99.0002  | 200  | 0.1666          | 11.4486 |
| 0.0028        | 199.0002 | 400  | 0.2083          | 13.5514 |
| 0.0007        | 299.0002 | 600  | 0.2815          | 20.7944 |
| 0.0008        | 399.0002 | 800  | 0.2882          | 19.3925 |


### Framework versions

- Transformers 4.46.0.dev0
- Pytorch 2.0.1
- Datasets 3.0.1
- Tokenizers 0.20.1