---
language:
- he
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- ivrit-ai/whisper-training
metrics:
- wer
model-index:
- name: Whisper Tiny Hebrew
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: ivrit-ai/whisper-training
      type: ivrit-ai/whisper-training
      args: 'config: he, split: train'
    metrics:
    - name: Wer
      type: wer
      value: 55.88158581116328
---

<!-- 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 Hebrew

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the ivrit-ai/whisper-training dataset.

## 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: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.973         | 0.13  | 500   | 0.8480          | 77.6213 |
| 0.9024        | 0.25  | 1000  | 0.7710          | 67.9838 |
| 0.8049        | 0.38  | 1500  | 0.7499          | 66.7384 |
| 0.7221        | 0.5   | 2000  | 0.7092          | 64.7953 |
| 0.7464        | 0.63  | 2500  | 0.6939          | 62.7543 |
| 0.7396        | 0.75  | 3000  | 0.6839          | 62.5261 |
| 0.7336        | 0.88  | 3500  | 0.6716          | 61.2350 |
| 0.6118        | 1.01  | 4000  | 0.6512          | 58.4637 |
| 0.6299        | 1.13  | 4500  | 0.6564          | 60.1721 |
| 0.6318        | 1.26  | 5000  | 0.6475          | 58.8550 |
| 0.6315        | 1.38  | 5500  | 0.6361          | 58.9724 |
| 0.6081        | 1.51  | 6000  | 0.6321          | 57.1596 |
| 0.6487        | 1.63  | 6500  | 0.6459          | 58.5616 |
| 0.6481        | 1.76  | 7000  | 0.6298          | 56.9379 |
| 0.5833        | 1.88  | 7500  | 0.6303          | 57.8965 |
| 0.5689        | 2.01  | 8000  | 0.6305          | 56.1750 |
| 0.5223        | 2.14  | 8500  | 0.6335          | 56.6967 |
| 0.574         | 2.26  | 9000  | 0.6248          | 55.3730 |
| 0.5841        | 2.39  | 9500  | 0.6320          | 55.6273 |
| 0.5533        | 2.51  | 10000 | 0.6254          | 55.8816 |


### Framework versions

- Transformers 4.40.0.dev0
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2