arabic-nano-gpt
This model is a fine-tuned version of openai-community/gpt2 on the arabic wikimedia/wikipedia dataset.
Repository on GitHub: e-hossam96/arabic-nano-gpt
The model achieves the following results on the held-out test set:
- Loss: 3.28796
How to Use
import torch
from transformers import pipeline
model_ckpt = "e-hossam96/arabic-nano-gpt-v0"
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
lm = pipeline(task="text-generation", model=model_ckpt, device=device)
prompt = """المحرك النفاث هو محرك ينفث الموائع (الماء أو الهواء) بسرعة فائقة \
لينتج قوة دافعة اعتمادا على مبدأ قانون نيوتن الثالث للحركة. \
هذا التعريف الواسع للمحركات النفاثة يتضمن أيضا"""
output = lm(prompt, max_new_tokens=128)
print(output[0]["generated_text"])
Model description
- Embedding Size: 256
- Attention Heads: 4
- Attention Layers: 4
Training and evaluation data
The entire wikipedia dataset was split into three splits based on the 90-5-5 ratios.
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 24
Training Loss
Validation Loss
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.0
- Datasets 3.0.1
- Tokenizers 0.20.1