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---

base_model: openai/whisper-tiny
datasets:
- mozilla-foundation/common_voice_11_0
language:
- az
license: apache-2.0
metrics:
- wer
tags:
- hf-asr-leaderboard
- generated_from_trainer
model-index:
- name: Whisper Tiny Az - Pologue
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: az
      split: None
      args: 'config: az, split: test'
    metrics:
    - type: wer
      value: 118.18181818181819
      name: Wer
---


<!-- 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 Tiny Az - Pologue

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5076
- Wer: 118.1818

## 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: 8

- seed: 42

- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08

- lr_scheduler_type: linear

- lr_scheduler_warmup_steps: 50
- training_steps: 100

- mixed_precision_training: Native AMP



### Training results



| Training Loss | Epoch   | Step | Validation Loss | Wer      |

|:-------------:|:-------:|:----:|:---------------:|:--------:|

| 0.0177        | 33.3333 | 100  | 1.5076          | 118.1818 |





### Framework versions



- Transformers 4.43.0.dev0

- Pytorch 2.3.1+cpu

- Datasets 2.20.0

- Tokenizers 0.19.1