--- 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
View Raw Training Log (JSON) ```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 }