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Model: EhabSuliman/my_awesome_eli5_clm-model
Source: Original Platform

README.md

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+---
+library_name: transformers
+license: apache-2.0
+language:
+- en
+base_model: distilbert/distilgpt2
+tags:
+- text-generation
+- causal-lm
+- arabic
+- fine-tuned
+- generated_from_trainer
+model-index:
+- name: my_awesome_eli5_clm-model
+  results: []
+---
+
+# my_awesome_eli5_clm-model
+
+A Causal Language Model fine-tuned on Arabic text, based on [distilbert/distilgpt2](https://huggingface.co/distilbert/distilgpt2).  
+Fine-tuned by **EhabSuliman** as part of an LLM course project.
+
+## Model Description
+
+- **Model type:** Causal Language Model (CLM)
+- **Base model:** [distilbert/distilgpt2](https://huggingface.co/distilbert/distilgpt2)
+- **Language:** English 
+- **Fine-tuned by:** [EhabSuliman](https://huggingface.co/EhabSuliman)
+- **License:** Apache 2.0
+
+## Intended Uses & Limitations
+
+**Intended uses:**
+- Arabic text generation
+- Language modeling research
+- Educational/learning purposes
+
+**Limitations:**
+- Trained on a relatively small dataset
+- Loss is still relatively high (3.8027), meaning the model may generate inaccurate or repetitive text
+- Not recommended for production use without further fine-tuning
+
+## How to Use
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("EhabSuliman/my_awesome_eli5_clm-model")
+model = AutoModelForCausalLM.from_pretrained("EhabSuliman/my_awesome_eli5_clm-model")
+
+prompt = "Somatic hypermutation allows the immune system to"
+inputs = tokenizer(prompt, return_tensors="pt").input_ids
+outputs = model.generate(
+    inputs,
+    max_new_tokens=100,
+    do_sample=True,
+    top_k=50,
+    top_p=0.95
+)
+print(tokenizer.batch_decode(outputs, skip_special_tokens=True))
+```
+
+## Training and Evaluation Data
+
+Fine-tuned on an Arabic text dataset using the ELI5 (Explain Like I'm 5) format.
+
+## Training Procedure
+
+### Training Hyperparameters
+
+The following hyperparameters were used during training:
+
+- **Learning rate:** 2e-05
+- **Train batch size:** 8
+- **Eval batch size:** 8
+- **Seed:** 42
+- **Optimizer:** AdamW (fused) with betas=(0.9, 0.999), epsilon=1e-08
+- **LR scheduler:** Linear
+- **Epochs:** 3
+
+### Training Results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 3.8556        | 1.0   | 1327 | 3.8101          |
+| 3.7851        | 2.0   | 2654 | 3.8035          |
+| 3.7514        | 3.0   | 3981 | 3.8027          |
+
+> The model shows steady improvement across epochs with validation loss decreasing from 3.8101 → 3.8027.
+
+### Framework Versions
+
+- Transformers 5.9.0
+- PyTorch 2.11.0+cu128
+- Datasets 4.0.0
+- Tokenizers 0.22.2
+
+## Author
+
+**Ehab Suliman** — Machine Learning Engineer  
+🔗 [HuggingFace Profile](https://huggingface.co/EhabSuliman)