Update README.md

README.md

@@ -1,23 +1,34 @@
 ---
 license: mit
 datasets:
-- glaiveai/glaive-function-calling-v2
-- nickrosh/Evol-Instruct-Code-80k-v1
+  - glaiveai/glaive-function-calling-v2
+  - nickrosh/Evol-Instruct-Code-80k-v1
 language:
-- en
+  - en
 base_model:
-- LiquidAI/LFM2.5-1.2B-Instruct
+  - LiquidAI/LFM2.5-1.2B-Instruct
+tags:
+  - tool-use
+  - code
+  - unsloth
+  - liquid
+  - fine-tune
+library_name: unsloth
 ---
 
+# 🧠 LFM-2.5-1.2B-Coding-Tools
+
+This is a fine-tuned version of **Liquid LFM-2.5-1.2B-Instruct**, specialized for **Python coding** and **native tool calling**. It was trained using [Unsloth](https://github.com/unslothai/unsloth) on a hybrid dataset of coding instructions and Pythonic function calls.
+
 ## 📉 Training Results & Metrics
 
-This model was fine-tuned on **Liquid LFM-2.5-1.2B-Instruct** using **Unsloth** and T4 GPUs. The following metrics were recorded during the final training run.
+This model was fine-tuned on a Google Colab **Tesla T4** instance. The following metrics were recorded during the final training run.
 
 | Metric | Value | Description |
 | :--- | :--- | :--- |
 | **Final Loss** | `0.7431` | The model's error rate at the final step. |
 | **Average Train Loss** | `0.8274` | The average error rate across the entire session. |
-| **Epochs** | `0.96` | completed ~1 full pass over the dataset. |
+| **Epochs** | `0.96` | Completed ~1 full pass over the dataset. |
 | **Global Steps** | `60` | Total number of optimizer updates. |
 | **Runtime** | `594s` (~10 min) | Total wall-clock time for training. |
 | **Samples/Second** | `0.808` | Throughput speed on T4 GPU. |