---
language: he
tags:
  - whisper
  - hebrew
  - acft
  - speech-recognition
library_name: transformers
base_model: yoad/whisper-small
---

# whisper-yoad-small-he-acft

ACFT (Audio Context Fine-Tuning) applied to [yoad/whisper-small](https://huggingface.co/yoad/whisper-small) for Hebrew speech recognition.

ACFT aligns partial-context encoder representations with full-context ones, improving short-utterance inference (e.g., keyboard dictation).

## Evaluation

WER on ivrit-ai/whisper-training test split (2000 samples, no normalization):

| Model | WER |
|-------|-----|
| yoad/whisper-small (base) | 0.2704 |
| yoad/whisper-small + ACFT (this model) | 0.2540 |

## Training

- **Method:** ACFT (encoder MSE alignment)
- **Dataset:** google/fleurs he_il
- **Epochs:** 8
- **Device:** Apple MPS (M4 Pro)

## Usage

```python
from transformers import WhisperForConditionalGeneration, WhisperProcessor

model = WhisperForConditionalGeneration.from_pretrained("amitkot/whisper-yoad-small-he-acft")
processor = WhisperProcessor.from_pretrained("amitkot/whisper-yoad-small-he-acft")
```