trm
Datasets
All datasets matching “trm”cleaned_turkish_embedding_model_training_data_colab
Citation
If you use this dataset in your research, please cite the following paper:
@inproceedings{baysan-gungor-2025-tr,
title = "{TR}-{MTEB}: A Comprehensive Benchmark and Embedding Model Suite for {T}urkish Sentence Representations",
author = "Baysan, Mehmet Selman and
Gungor, Tunga",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2025",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher =… See the full description on the dataset page: https://huggingface.co/datasets/trmteb/cleaned_turkish_embedding_model_training_data_colab.dl-trm-phase2-codebooks
DL-TRM Phase 2 Codebooks
This dataset repository contains Phase 2 transition VQ codebook artifacts for DL-TRM.
Contents are organized by vocabulary size:
V16/
V32/
V128/
V256/
Each folder includes:
z_traces.pt: discrete Z trace dataset for the Phase 1 route traces
codebook.pt: learned VQ codebook weights
transition_vq_model.pt: trained transition VQ model weights
diagnostics.json: code usage and final training diagnostics
z_trace_manifest.json: artifact manifest
checkpoints/:… See the full description on the dataset page: https://huggingface.co/datasets/omrisap/dl-trm-phase2-codebooks.turkish_embedding_model_training_datadl-trm-phase2-codebook-v32
DL-TRM Phase 2 Codebook V32
This standalone dataset contains the Phase 2 discrete Z traces for V32.
The Hugging Face dataset viewer reads data/train.jsonl.
Each row contains:
raw_puzzle_id
route_id
route_local_id
medoid_old_id
selected_stage_a_example_index
cluster_size
vocab_size
z_trace: a length-16 list of discrete Z token IDs
The original PyTorch artifacts remain in the repo:
z_traces.pt
codebook.pt
transition_vq_model.pt
diagnostics.json
z_trace_manifest.json
checkpoints/
swev-trm-trajectories-25models
SWE-Bench Verified TRM Trajectories (25 Models, Verified Labels)
Trajectories from 25 LLMs attempting SWE-Bench Verified tasks, formatted for
training a Trajectory Reward Model (TRM). Each record is one model's full
multi-turn attempt at one task, labeled with the real SWE-bench harness
verdict (scores.resolved).
Splits
Split
Records
Tasks
Pos
Neg
train
10,107
405
6,108
3,999
val
2,366
95
1,440
926
Train/val are task-disjoint (stable hash on task_id… See the full description on the dataset page: https://huggingface.co/datasets/tarsur385/swev-trm-trajectories-25models.nfcorpus-tr