Kurmanji Kurdish Speech Recognition Model
This model was created by fine-tuning facebook/wav2vec2-xls-r-300m on the Mozilla Common Voice 8.0 Kurmanji Kurdish dataset.

It is designed to convert spoken Kurmanji Kurdish audio into text accurately and efficiently.

🧠 Model Description

This model is part of the Ferhengy project — a Kurdish language learning and transcription tool.
It builds upon multilingual speech representation learning using Wav2Vec2 XLS-R 300M and adapts it specifically for Kurmanji Kurdish.

🎯 Intended Uses

Speech-to-text for Kurmanji Kurdish content (education, linguistics, or accessibility)
Transcription of Kurdish audio for apps, media, or research
Integration in applications that promote Kurdish digital language tools

🧾 Training Data

The model was trained on Common Voice Kurmanji Kurdish (v8.0), using:

train.tsv
dev.tsv
invalidated.tsv
reported.tsv
other.tsv

Only samples with positive upvotes were used, and duplicates were removed to ensure high-quality data.

⚙️ Training Details

Training configuration (for reproducibility):

Hyperparameter	Value
learning_rate	9.6e-5
train_batch_size	16
eval_batch_size	16
gradient_accumulation_steps	16
lr_scheduler_type	cosine_with_restarts
num_epochs	100
seed	13
mixed_precision_training	Native AMP

Results

Step	Training Loss	Validation Loss	WER
1200	0.2263	0.2924	0.3886

🧩 Framework Versions

Transformers: 4.16.0
PyTorch: 1.10.0
Datasets: 1.18.1
Tokenizers: 0.10.3

🧪 Evaluation Example

To evaluate on Common Voice 8.0 (Kurdish):

python eval.py --model_id maniwebdev/xlsr_kurmanji_kurdish_custom --dataset mozilla-foundation/common_voice_8_0 --config kmr --split test