Stage 01

Full Model Fine-Tuning

Fine-tune complete transformer models for classification and generation. Build custom training loops with mixed precision.

10notebooks

7hestimated

1050 min

Full Fine-Tuning: Classification

Fine-tune DistilBERT on IMDB sentiment with HuggingFace Trainer. Understand the full classification pipeline.

DistilBERTSequence ClassificationHuggingFace Trainerevaluate

Study Colab

1150 min

Full Fine-Tuning: Generation

Fine-tune GPT-2 for causal language modeling. Implement greedy, beam search, and sampling decoding strategies.

GPT-2Causal LMGreedy DecodingBeam Search+1

Study Colab

1245 min

Custom Training Loop

Build a manual training loop with gradient clipping, mixed precision (AMP), and checkpoint saving.

AMPGradient ClippingCheckpointingManual Training Loop

Study Colab

1340 min

Custom Loss Functions

Implement weighted cross-entropy, focal loss, and label smoothing. Understand when to use each.

Weighted CEFocal LossLabel SmoothingLoss Engineering

Study Colab

1440 min

Imbalanced Classification

Threshold tuning, class-weighted loss, and evaluation metrics for heavily imbalanced datasets.

Threshold TuningPR CurveClass WeightsF1 Score

Study Colab

1535 min

Mixed Precision Training

FP16/BF16 training with GradScaler. Understand loss scaling and numerical stability.

FP16BF16GradScalerMixed Precision+1

Study Colab

1630 min

Gradient Accumulation

Train with effective large batch sizes on limited GPU memory using gradient accumulation.

Gradient AccumulationEffective Batch SizeMemory Efficiency

Study Colab

1735 min

Regularization Techniques

Dropout, weight decay, early stopping, and learning rate scheduling to prevent overfitting.

DropoutWeight DecayEarly StoppingRegularization

Study Colab

1840 min

Evaluation Metrics

Perplexity, BLEU, ROUGE, F1, precision/recall. Build a comprehensive evaluation harness.

PerplexityBLEUROUGEF1+1

Study Colab

1935 min

Curriculum Learning

Train on easy examples first, gradually introducing harder ones. Improves convergence and generalization.

Curriculum LearningDifficulty ScoringTraining Schedule

Study Colab

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Foundations & Environment

Parameter-Efficient Fine-Tuning