| --- |
| license: mit |
| datasets: |
| - glaiveai/glaive-function-calling-v2 |
| - nickrosh/Evol-Instruct-Code-80k-v1 |
| language: |
| - en |
| base_model: |
| - 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 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. | |
| | **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. | |
| | **Gradient Norm** | `0.345` | Indicates stable training (no exploding gradients). | |
| | **Learning Rate** | `3.64e-6` | Final learning rate after decay. | |
| | **Total FLOS** | `2.07e15` | Total floating-point operations computed. | |
|
|
| ### 🛠️ Hardware & Framework |
| * **Hardware:** NVIDIA Tesla T4 (Google Colab Free Tier) |
| * **Framework:** Unsloth (PyTorch) |
| * **Quantization:** 4-bit (QLoRA) |
| * **Optimizer:** AdamW 8-bit |
|
|
| <details> |
| <summary><strong>View Raw Training Log (JSON)</strong></summary> |
|
|
| ```json |
| { |
| "_runtime": 348, |
| "_step": 60, |
| "_timestamp": 1770910365.0772636, |
| "_wandb.runtime": 348, |
| "total_flos": 2069937718053888, |
| "train/epoch": 0.96, |
| "train/global_step": 60, |
| "train/grad_norm": 0.3452725112438202, |
| "train/learning_rate": 0.000003636363636363636, |
| "train/loss": 0.7431, |
| "train_loss": 0.8273822158575058, |
| "train_runtime": 594.2969, |
| "train_samples_per_second": 0.808, |
| "train_steps_per_second": 0.101 |
| } |
