Configuration

DNABERT-2 117M, one layer pruned, fine-tuned to convergence (Hegde et al. 2025)

zhihan1996/DNABERT-2-117M with one encoder layer removed, fine-tuned to convergence of the validation loss on 2 × Quadro RTX 8000.

1 evaluation · 1 result

Overview

An explanatory profile has not yet been reviewed for this record.

Consult the linked sources for architecture or protocol details. Missing evidence is not evidence of a missing capability.

Evaluations and results

1 evaluation · 1 result. Different protocols are not a single leaderboard.

Filter evaluations

Tested model or methodProtocolDatasetEvaluation setupMetricEvidence origin

Applied filters: All linked evaluations

Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: DNABERT-2 117M, one layer pruned, fine-tuned to convergence (Hegde et al. 2025)	Protocol: Fine-tuning wall time to convergence on the Enformer eQTL dataset (Hegde et al. 2025 Methods) Dataset: Enformer eQTL causal-variant dataset, Genomics Long-Range Benchmark version (Hegde et al. 2025)	around 1 Runtime (Fine-tuning to convergence, average per pruned model) hour · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DNABERT-2 pruned models, fine-tuning time to convergence (Hegde et al. 2025) gfm-guide-20261014-protocol-hegde-eqtl-finetune-convergence-time Aggregation: Not reported Reaping the Fruits of LLM Pruning: Towards Small Language Models for Efficient Non-Coding Variant Effect Prediction · Methods paragraph 3: 'taking around 1 h per pruned model on average'

Source checking is not independent reproduction. Release 2026-10-22-1b7cf027e4f6.

Use this configuration

How it works, versions and access

Strengths, limitations and unresolved questions

Evidence

Source checking verifies the cited claim or transcription. It does not establish independent reproduction.

Evidence table

Inspect claims, sources and review details

Trace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.

One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.

0 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-10-22-1b7cf027e4f6
Property and statement	Original source and location	Review and provenance

No evidence rows match these filters. Choose another scope or clear the search.

How to read the evidence

Sources and history

Release 2026-10-22-1b7cf027e4f6 · Record review: source checked

1 source record and release history

Reaping the Fruits of LLM Pruning: Towards Small Language Models for Efficient Non-Coding Variant Effect Prediction · Original source · Genes 16(11):1358, 2025; PMC12652071 full-text XML

Download this release (gzip)

Technical metadata and extraction receipts

Stable ID: gfm-guide-20261014-config-hegde-dnabert-2-pruned-convergence

areas: dna-genomes
contexts: research
method types: foundation_model
reported name: DNABERT-2 (pruned model)
checkpoint: zhihan1996/DNABERT-2-117M
hardware: description: 2 × Quadro RTX 8000 GPUs
source locator: Methods paragraph 3; Appendix A.1
missing metadata: version: reason: unreported; note: Hugging Face repository named without a revision

Related records

configuration of: DNABERT-2
system: DNABERT-2 pruned models, fine-tuning time to convergence (Hegde et al. 2025)

Suggest a correction