[SUBMISSION] MODULE 1

[Knight7561]

December 2024 Student Submission

Module Completed

• Module 1: Instruction Tuning
• Module 2: Preference Alignment
• Module 3: Parameter-efficient Fine-tuning
• Module 4: Evaluation
• Module 5: Vision-language Models
• Module 6: Synthetic Datasets
• Module 7: Inference
• Module 8: Deployment

Changes Made

Describe what you've done in this PR:

1. What concepts did you learn?

• Tokenisation, Reading datasets from HF, fine tuning smol models and how tokinzer module is contained

2. What changes or additions did you make?

• Added comments for better understanding, will add additional examples in the future work

3. Any challenges you faced?

• Nothing for this module

Notebooks Added/Modified

List any notebooks you've added or modified:

• Added new example in module_name/student_examples/my_example.ipynb
• Modified existing notebook with additional examples
• Added documentation or comments

Checklist

• I have read the module materials
• My code runs without errors
• I have pushed models and datasets to the huggingface hub
• My PR is based on the december_2024 branch

Questions or Discussion Points

Add any questions you have or points you'd like to discuss:
1.
2.

Additional Notes

Any other information that might be helpful for reviewers:

[burtenshaw]

Structurally this looks great.

@ShankarChavan Could you peer-review the notebooks please?

[Knight7561]

@burtenshaw @ShankarChavan Is my PR good ?

[ShankarChavan]

In your SFT_finetuning_example the model has not shown any improvement on loss function. Also, the response from model for the given test-questions were giving repeated response as model has not learned yet. Please try to fix these issues from your end.