transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer hu dataset:mozilla-foundation/common_voice_16_0 base_model:openai/whisper-tiny license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
language:
- hu
widget:
- example_title: Sample 1
  src: https://huggingface.co/datasets/Hungarians/samples/resolve/main/Sample1.flac
- example_title: Sample 2
  src: https://huggingface.co/datasets/Hungarians/samples/resolve/main/Sample2.flac
metrics:
- wer
pipeline_tag: automatic-speech-recognition
model-index:
- name: Whisper Tiny Hu v2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 16.0 - Hungarian
      type: mozilla-foundation/common_voice_16_0
      config: hu
      split: test
      args: hu
    metrics:
    - name: Wer
      type: wer
      value: 15.7367
      verified: true

---

<!-- 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 Hu v2

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 16.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1930
- Wer Ortho: 17.3040
- Wer: 15.7367

## 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: 4e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 500
- training_steps: 15000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:-------:|
| 0.5487        | 0.33  | 1000  | 0.5970          | 55.5492   | 52.2206 |
| 0.3922        | 0.67  | 2000  | 0.4419          | 43.1109   | 39.9911 |
| 0.3242        | 1.0   | 3000  | 0.3662          | 37.2727   | 34.2040 |
| 0.2517        | 1.34  | 4000  | 0.3329          | 33.7890   | 30.8746 |
| 0.2455        | 1.67  | 5000  | 0.2925          | 30.6185   | 28.0196 |
| 0.1398        | 2.01  | 6000  | 0.2600          | 27.1709   | 24.5983 |
| 0.1421        | 2.34  | 7000  | 0.2491          | 26.1291   | 23.6347 |
| 0.1578        | 2.68  | 8000  | 0.2342          | 24.4761   | 22.0783 |
| 0.0732        | 3.01  | 9000  | 0.2163          | 22.1245   | 19.8547 |
| 0.0941        | 3.35  | 10000 | 0.2143          | 22.2058   | 19.8399 |
| 0.0936        | 3.68  | 11000 | 0.2094          | 20.5980   | 18.7756 |
| 0.0489        | 4.02  | 12000 | 0.2027          | 18.9630   | 17.2665 |
| 0.0548        | 4.35  | 13000 | 0.1981          | 18.4933   | 16.5491 |
| 0.0585        | 4.69  | 14000 | 0.1953          | 17.7195   | 15.7693 |
| 0.0356        | 5.02  | 15000 | 0.1930          | 17.3040   | 15.7367 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
