---
language:
- he
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- ivrit-ai/whisper-training
metrics:
- wer
model-index:
- name: Whisper Small 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: 40.6755346896192
---

<!-- 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 Hebrew

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the ivrit-ai/whisper-training dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4241
- Wer: 37.8652

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.4946        | 0.13  | 500   | 0.4572          | 46.4463 |
| 0.4629        | 0.25  | 1000  | 0.4492          | 43.7663 |
| 0.4067        | 0.38  | 1500  | 0.4337          | 42.6317 |
| 0.3663        | 0.5   | 2000  | 0.3892          | 41.8427 |
| 0.3857        | 0.63  | 2500  | 0.4017          | 40.7473 |
| 0.3795        | 0.75  | 3000  | 0.4011          | 39.4823 |
| 0.368         | 0.88  | 3500  | 0.3967          | 39.9778 |
| 0.2353        | 1.01  | 4000  | 0.3801          | 38.3281 |
| 0.2405        | 1.13  | 4500  | 0.4062          | 41.5428 |
| 0.2512        | 1.26  | 5000  | 0.3975          | 38.6215 |
| 0.2433        | 1.38  | 5500  | 0.4035          | 38.5824 |
| 0.2368        | 1.51  | 6000  | 0.3983          | 37.8652 |
| 0.2592        | 1.63  | 6500  | 0.4184          | 39.1041 |
| 0.2629        | 1.76  | 7000  | 0.4000          | 39.5475 |
| 0.2318        | 1.88  | 7500  | 0.4012          | 39.1954 |
| 0.1658        | 2.01  | 8000  | 0.3941          | 39.1367 |
| 0.1546        | 2.14  | 8500  | 0.4226          | 39.8865 |
| 0.1665        | 2.26  | 9000  | 0.4295          | 40.9755 |
| 0.1642        | 2.39  | 9500  | 0.4314          | 41.1255 |
| 0.1694        | 2.51  | 10000 | 0.4241          | 40.6755 |


### Framework versions

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