Model: ahmadhehe/tinyllama-1.1b-dpo-hh-rlhf Source: Original Platform
base_model, library_name, tags
| base_model | library_name | tags | |||||
|---|---|---|---|---|---|---|---|
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | transformers |
|
Best DPO Model — DPO-D4
TinyLlama-1.1B-Chat-v1.0 first SFT-tuned on dolly-15k, then aligned via Direct Preference Optimization (DPO) on Anthropic/hh-rlhf.
Authors
- Ahmad Murtaza (24478)
- Simra Sheikh (27135)
Project Context
This model was developed as part of Assignment 04 for the NLP with Deep Learning course at the Institute of Business Administration (IBA). The assignment involves building a full SFT → DPO fine-tuning pipeline on TinyLlama-1.1B-Chat-v1.0 and evaluating the impact of instruction tuning and preference alignment.
Training config
trial : DPO-D4
sft_base : SFT-T4
beta : 0.5
learning_rate : 5e-05
epochs : 1
val_loss : 0.7304
Evaluation (10-prompt test set, merged models)
| Model | BLEU-4 | BERTScore F1 |
|---|---|---|
| Base (TinyLlama-1.1B) | 2.1400 | 85.4700 |
| Best SFT (SFT-T4) | 2.4200 | 87.1100 |
| Best DPO (DPO-D4) | 4.2200 | 86.9600 |
Description
Languages
Jinja
100%