Update README.md

README.md

@@ -1,209 +1,154 @@
+
 ---
-base_model: openai-community/gpt2
+license: apache-2.0          # أو أي ترخيص تفضله (يمكنك تغييره)
+language:
+  - en
 library_name: peft
-pipeline_tag: text-generation
 tags:
-- base_model:adapter:openai-community/gpt2
-- lora
-- sft
-- transformers
-- trl
+  - causal-lm
+  - text-generation
+  - lora
+  - gpt2
+  - fine-tuned
+base_model: openai-community/gpt2
+pipeline_tag: text-generation
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-
-
-## Model Details
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-
-
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+# GPT-2 FineWeb (machkour's continued pretraining variant)
 
-## How to Get Started with the Model
+## Model Description
 
-Use the code below to get started with the model.
+This is a **continued pretraining** (fine-tuning for next-token prediction) of the original **GPT-2** (small, 124M parameters) on a high-quality subset of **FineWeb** dataset.
 
-[More Information Needed]
+- **Base model**: openai-community/gpt2 (original GPT-2 small)
+- **Training method**: PEFT + LoRA (r=32, alpha=32, targets: c_attn, c_proj, c_fc)
+- **Quantization during training**: 4-bit NF4 + double quant + bfloat16 compute
+- **Training objective**: Causal language modeling (next token prediction)
+- **Purpose**: Improve general text continuation / next-word prediction quality before personality / instruction tuning in the next stage.
 
-## Training Details
+## When & How Was It Created?
 
-### Training Data
+- **Creation date**: February 26, 2026
+- **Training duration**: ≈ 60 minutes (600 training steps)
+- **Hardware**: Google Colab T4 GPU (15 GB VRAM)
+- **Training start → end**: ~39–40 minutes wall-clock time for the final run (after map/tokenization overhead)
+- **Created by**: @younes
+## Training Data
 
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+- **Dataset**: HuggingFaceFW/fineweb — configuration: `sample-10BT`
+- **Processed subset**: 700,000 documents (after filtering short texts)
+- **Total tokens**: ≈ 416 million tokens (estimated from previous runs)
+- **Format**: `.jsonl.gz` with single field `{"text": "..."}`
+- **Language**: Primarily English (fineweb is English-dominant)
+- **Data source date**: Mostly web crawl snapshots from ~2013 (old but very clean high-quality subset)
 
-[More Information Needed]
+**Note**: This is **not** instruction-tuned or chat-tuned. It is still a raw language model optimized for free-form text continuation.
 
-### Training Procedure
+## Model Size & Files
 
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+- **Base parameters**: 124M (GPT-2 small)
+- **Trainable LoRA parameters**: ≈ 4.72M (3.65% of total)
+- **Total effective parameters**: still 124M (LoRA is additive)
+- **Disk size (saved folder)**: ~250–350 MB (4-bit base + LoRA adapters)
+- **Saved directory**: `gpt2-fineweb-final`
+- **Main files**:
+  - `adapter_config.json`
+  - `adapter_model.bin` (or safetensors)
+  - `config.json`
+  - `generation_config.json`
+  - `pytorch_model.bin` (quantized base)
+  - `tokenizer.json`, `vocab.json`, `merges.txt`
 
-#### Preprocessing [optional]
+## How to Use / Load the Model
 
-[More Information Needed]
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
 
+base_model_name = "openai-community/gpt2"
+adapter_path = "machkour/gpt2-fineweb-416M-tokens"   # ← change to your repo after upload
 
-#### Training Hyperparameters
+tokenizer = AutoTokenizer.from_pretrained(base_model_name)
 
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+model = AutoModelForCausalLM.from_pretrained(
+    base_model_name,
+    device_map="auto",
+    torch_dtype="auto"
+)
 
-#### Speeds, Sizes, Times [optional]
+model = PeftModel.from_pretrained(model, adapter_path)
 
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+# Optional: merge LoRA weights into base model (for faster inference)
+# model = model.merge_and_unload()
 
-[More Information Needed]
+# Example generation
+prompt = "The future of artificial intelligence is"
+inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
 
-## Evaluation
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=120,
+    do_sample=True,
+    temperature=0.85,
+    top_p=0.92
+)
 
-<!-- This section describes the evaluation protocols and provides the results. -->
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
 
-### Testing Data, Factors & Metrics
+## Intended Use & Limitations
 
-#### Testing Data
+- Best for: open-ended text generation, story continuation, code / prose completion
+- Not suitable (yet) for: chat / instruction following, Q&A, Arabic-dominant tasks
+- Next planned step: personality / role injection + instruction tuning
 
-<!-- This should link to a Dataset Card if possible. -->
+## Training Hyperparameters (final run)
 
-[More Information Needed]
+- Optimizer: adamw_8bit
+- Learning rate: 5e-5
+- Batch size: 4 × 4 (effective 16)
+- Steps: 600
+- Warmup steps: 50
+- Gradient checkpointing: yes
+- Mixed precision: bf16
 
-#### Factors
+## Results / Observations
 
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+- Loss decreased from ~3.89 → ~3.54 over 600 steps
+- Visible improvement in fluency and topical coherence compared to vanilla GPT-2
+- Still shows signs of repetition / old-web style (due to FineWeb age)
 
-[More Information Needed]
+## How to Cite / Reference
+
+If you use this model:
+
+```
+@misc{gpt2-fineweb-machkour,
+  author       = {machkour},
+  title        = {GPT-2 continued on FineWeb (416M tokens)},
+  year         = {2026},
+  month        = {February},
+  howpublished = {\url{https://huggingface.co/machkour/gpt2-fineweb-416M-tokens}},
+}
+```
 
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
+---
 
-[More Information Needed]
+Good luck with the upload!
 
-## Model Card Authors [optional]
+After saving this as README.md in your model folder, you can push everything with:
 
-[More Information Needed]
+```python
+from huggingface_hub import login, upload_folder
 
-## Model Card Contact
+login()  # paste your HF token
 
-[More Information Needed]
-### Framework versions
+upload_folder(
+    folder_path="gpt2-fineweb-final",
+    repo_id="machkour/gpt2-fineweb-416M-tokens",
+    repo_type="model",
+    commit_message="Upload fine-tuned GPT-2 on FineWeb"
+)
+```
 
-- PEFT 0.18.1
+(Install `huggingface_hub` if needed: `!pip install huggingface_hub`)