datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
MaCBench-Ablations
MaCBench-Ablations
A Chemistry and Materials Benchmark for evaluating Vision Large Language Models
⚠️ IMPORTANT NOTICE - NOT FOR TRAINING
🚫 THIS DATASET IS STRICTLY FOR EVALUATION PURPOSES ONLY 🚫
DO NOT USE THIS DATASET FOR TRAINING OR FINE-TUNING MODELS
This benchmark is designed exclusively for evaluation and testing of existing models. Using this data for training would compromise the integrity of the benchmark and invalidate evaluation… See the full description on the dataset page: https://huggingface.co/datasets/jablonkagroup/MaCBench-Ablations.MaCBench-Prompt-Ablations
MaCBench-Prompt-Ablations
A Chemistry and Materials Benchmark for evaluating Vision Large Language Models
⚠️ IMPORTANT NOTICE - NOT FOR TRAINING
🚫 THIS DATASET IS STRICTLY FOR EVALUATION PURPOSES ONLY 🚫
DO NOT USE THIS DATASET FOR TRAINING OR FINE-TUNING MODELS
This benchmark is designed exclusively for evaluation and testing of existing models. Using this data for training would compromise the integrity of the benchmark and invalidate… See the full description on the dataset page: https://huggingface.co/datasets/jablonkagroup/MaCBench-Prompt-Ablations.llama-3.1-8b-funding-extraction-sft-ablations
LLaMA 3.1 8B Funding Extraction SFT Ablations
Ablation study results for LoRA SFT of Meta LLaMA 3.1 8B Instruct on structured funding metadata extraction from scholarly text.
The model extracts four fields: funder_name, award_ids, funding_scheme, and award_title.
Key findings
Factor
Best config
Avg F1
Overall best
synthetic, twostage (2+1 epochs), LoRA r=64, lr=3e-5
0.588
Data type
Synthetic >> non-synthetic (+0.126 avg F1)
—
LoRA rank
r=64 > r=32 > r=16
—… See the full description on the dataset page: https://huggingface.co/datasets/cometadata/llama-3.1-8b-funding-extraction-sft-ablations.