Update README.md

README.md

@@ -1,3 +1,72 @@
----
-license: mit
----
+---
+license: mit
+---
+# Model Card
+
+## Overview
+
+This model is a 156M-parameter English-language causal language model trained on a large-scale text corpus and instruction-tuned for general question answering and task completion.
+
+---
+
+## Model Details
+
+* **Model size:** 156M parameters
+* **Architecture:** Transformer (causal LM)
+* **Tokenizer:** GPT-2 tokenizer
+* **Languages:** English only
+
+---
+
+## Training Data
+
+### Pretraining
+
+* Dataset: The Pile (10B token subset)
+* Domain: mixed-domain text (web, books, articles, code, etc.)
+
+### Instruction Fine-tuning
+
+* Dataset: Alpaca (cleaned subset)
+* Size: ~50,000 instruction–response examples
+* Formatting: instruction-style prompt/response pairs
+
+---
+
+## Training Setup
+
+### Pretraining
+
+* Steps: **218,000**
+* Final training loss: **2.6**
+
+### Post-training (Instruction Fine-tuning)
+
+* Steps: **2,500**
+* Final training loss: **1.9**
+
+---
+
+## Evaluation
+
+| Benchmark | Score    |
+| --------- | -------- |
+| HellaSwag | **28.5** |
+
+---
+
+## Intended Use
+
+* Instruction-style prompting
+* Basic question answering
+* Text generation and summarization
+* Lightweight assistant-style tasks (English)
+
+---
+
+## Limitations
+
+* Small model size limits reasoning and factual reliability
+* May produce incorrect or inconsistent answers
+* Instruction-following quality depends strongly on prompt format
+* Not suitable for high-stakes or safety-critical use