---
language:
- bg
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Bg - Yonchevisky_tes2t
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: bg
      split: test
      args: 'config: bg, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 61.83524504692388
---

<!-- 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 Small Bg - Yonchevisky_tes2t

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: 0.7377
- Wer: 61.8352

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8067        | 0.37  | 100  | 1.6916          | 137.6897 |
| 0.9737        | 0.73  | 200  | 1.1197          | 78.3571  |
| 0.7747        | 1.1   | 300  | 0.9763          | 73.8906  |
| 0.6672        | 1.47  | 400  | 0.8972          | 70.7102  |
| 0.6196        | 1.84  | 500  | 0.8329          | 67.4545  |
| 0.4849        | 2.21  | 600  | 0.7968          | 66.6029  |
| 0.4402        | 2.57  | 700  | 0.7597          | 62.7795  |
| 0.4601        | 2.94  | 800  | 0.7385          | 61.8642  |
| 0.3545        | 3.31  | 900  | 0.7394          | 61.5050  |
| 0.3596        | 3.68  | 1000 | 0.7377          | 61.8352  |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2