Serendip-LLM-CPT-SFT-v2/training_scripts/TRAINING_LOG.md

Training Log Summary

Final Training Run (train_v2_fast.py)

Start: February 18, 2026, ~17:30 End: February 19, 2026, ~20:00 Duration: 26.5 hours

Loss Progression

Epoch	Loss
0.95	0.28
1.90	0.24
3.00	0.27

Final training loss: 0.27

Configuration Used

num_train_epochs = 3
per_device_train_batch_size = 8
gradient_accumulation_steps = 4  # Effective batch = 32
learning_rate = 2e-5
max_length = 384  # tokens
warmup_steps = 200
weight_decay = 0.01

# LoRA Config
lora_r = 64
lora_alpha = 128
lora_target_modules = [
    "q_proj", "k_proj", "v_proj", 
    "o_proj", "gate_proj", "up_proj"
]
lora_dropout = 0.05

Hardware

• GPU: NVIDIA A100 SXM 80GB
• Training framework: Transformers + PEFT
• Mixed precision: FP16

Dataset

• Source: Chamaka8/Serendip-sft-sinhala
• File: serendipllm_sft_final_train_v2.json
• Examples: 309,328
• News classification: 45,080 examples
• General Sinhala: 205,403 examples
• QA pairs: 29,390 examples