Nanthasit/eval_results

Benchmark Results (cross-model)

Nanthasit/sakthai-context-0.5b-merged

Benchmark Results

Benchmark: sakthai-bench-v2 · 500 samples · run 2026-08-01

Overall (strict): 40.74 · Selection: 40.74 · Arguments: 59.91

Category	Count	Selection	Arguments	Strict
irrelevance_no_tools	50	100.00	100.00	100.00
irrelevance_tools	150	41.33	100.00	41.33
parallel	137	35.77	35.77	35.77
simple	122	21.31	21.31	21.31
held_out	-	10.71	10.71	10.71

Nanthasit/sakthai-context-1.5b-merged

Benchmark Results

Benchmark: sakthai-bench-v2 · 500 samples · run 2026-08-01

Overall (strict): 43.79 · Selection: 43.79 · Arguments: 44.66

Category	Count	Selection	Arguments	Strict
irrelevance_no_tools	50	100.00	100.00	100.00
irrelevance_tools	150	97.33	100.00	97.33
parallel	137	0.00	0.00	0.00
simple	122	4.10	4.10	4.10
held_out	-	7.14	7.14	7.14

Nanthasit/sakthai-context-7b-merged

Benchmark Results

Benchmark: sakthai-bench-v2 · 500 samples · run 2026-08-01

Overall (strict): 38.78 · Selection: 38.78 · Arguments: 45.53

Category	Count	Selection	Arguments	Strict
irrelevance_no_tools	50	100.00	100.00	100.00
irrelevance_tools	150	79.33	100.00	79.33
parallel	137	0.00	0.00	0.00
simple	122	7.38	7.38	7.38
held_out	-	10.71	10.71	10.71

Nanthasit/sakthai-plus-1.5b

Benchmark Results

Benchmark: sakthai-bench-v2 · 500 samples · run 2026-08-01

Overall (strict): 39.65 · Selection: 39.65 · Arguments: 61.66

Category	Count	Selection	Arguments	Strict
irrelevance_no_tools	50	100.00	100.00	100.00
irrelevance_tools	150	32.67	100.00	32.67
parallel	137	43.80	43.80	43.80
simple	122	18.85	18.85	18.85
held_out	-	16.07	16.07	16.07

Benchmark Results

Benchmark: sakthai-bench-v2 · 500 samples · run 2026-08-01

Overall (strict): 40.74 · Selection: 40.74 · Arguments: 59.91

Category	Count	Selection	Arguments	Strict
irrelevance_no_tools	50	100.00	100.00	100.00
irrelevance_tools	150	41.33	100.00	41.33
parallel	137	35.77	35.77	35.77
simple	122	21.31	21.31	21.31
held_out	-	10.71	10.71	10.71

Nanthasit/sakthai-context-1.5b-merged

Benchmark Results

Benchmark: sakthai-bench-v2 · 500 samples · run 2026-08-01

Overall (strict): 43.79 · Selection: 43.79 · Arguments: 44.66

Category	Count	Selection	Arguments	Strict
irrelevance_no_tools	50	100.00	100.00	100.00
irrelevance_tools	150	97.33	100.00	97.33
parallel	137	0.00	0.00	0.00
simple	122	4.10	4.10	4.10
held_out	-	7.14	7.14	7.14

Nanthasit/sakthai-context-7b-merged

Benchmark Results

Benchmark: sakthai-bench-v2 · 500 samples · run 2026-08-01

Overall (strict): 38.78 · Selection: 38.78 · Arguments: 45.53

Category	Count	Selection	Arguments	Strict
irrelevance_no_tools	50	100.00	100.00	100.00
irrelevance_tools	150	79.33	100.00	79.33
parallel	137	0.00	0.00	0.00
simple	122	7.38	7.38	7.38
held_out	-	10.71	10.71	10.71

Nanthasit/sakthai-plus-1.5b

Benchmark Results

Benchmark: sakthai-bench-v2 · 500 samples · run 2026-08-01

Overall (strict): 39.65 · Selection: 39.65 · Arguments: 61.66

Category	Count	Selection	Arguments	Strict
irrelevance_no_tools	50	100.00	100.00	100.00
irrelevance_tools	150	32.67	100.00	32.67
parallel	137	43.80	43.80	43.80
simple	122	18.85	18.85	18.85
held_out	-	16.07	16.07	16.07

Benchmark Results

Benchmark: sakthai-bench-v2 · 500 samples · run 2026-08-01

Overall (strict): 40.74 · Selection: 40.74 · Arguments: 59.91

Category	Count	Selection	Arguments	Strict
irrelevance_no_tools	50	100.00	100.00	100.00
irrelevance_tools	150	41.33	100.00	41.33
parallel	137	35.77	35.77	35.77
simple	122	21.31	21.31	21.31
held_out	-	10.71	10.71	10.71

Nanthasit/sakthai-context-1.5b-merged

Benchmark Results

Benchmark: sakthai-bench-v2 · 500 samples · run 2026-08-01

Overall (strict): 43.79 · Selection: 43.79 · Arguments: 44.66

Category	Count	Selection	Arguments	Strict
irrelevance_no_tools	50	100.00	100.00	100.00
irrelevance_tools	150	97.33	100.00	97.33
parallel	137	0.00	0.00	0.00
simple	122	4.10	4.10	4.10
held_out	-	7.14	7.14	7.14

Nanthasit/sakthai-context-7b-merged

Benchmark Results

Benchmark: sakthai-bench-v2 · 500 samples · run 2026-08-01

Overall (strict): 38.78 · Selection: 38.78 · Arguments: 45.53

Category	Count	Selection	Arguments	Strict
irrelevance_no_tools	50	100.00	100.00	100.00
irrelevance_tools	150	79.33	100.00	79.33
parallel	137	0.00	0.00	0.00
simple	122	7.38	7.38	7.38
held_out	-	10.71	10.71	10.71

Nanthasit/sakthai-plus-1.5b

Benchmark Results

Benchmark: sakthai-bench-v2 · 500 samples · run 2026-08-01

Overall (strict): 39.65 · Selection: 39.65 · Arguments: 61.66

Category	Count	Selection	Arguments	Strict
irrelevance_no_tools	50	100.00	100.00	100.00
irrelevance_tools	150	32.67	100.00	32.67
parallel	137	43.80	43.80	43.80
simple	122	18.85	18.85	18.85
held_out	-	16.07	16.07	16.07

Eval Results — SakThai Model Family

Evaluation results, health-check reports, and benchmark run logs for the SakThai model family

Dataset Summary

This repository stores evaluation results, health-check reports, and benchmark run logs for the SakThai model family. Every entry is a machine-readable YAML report produced by SakThai's automated cron workflows (benchmarks, health checks, inference probes) — the operational audit trail of the House of Sak.

Not a tabular dataset. All result files are YAML (.yaml), not JSONL/Parquet/CSV. Because the Hub's datasets-server only indexes tabular formats, this repo reports "no supported data files" — that is expected. These are point-in-time reports meant to be read with yaml.safe_load(), not rows for the dataset viewer. load_dataset() will not work here.

License: MIT Status: Active (auto-updated by cron workflows)

Quick Look

Report	Last Modified	Size
README.md	current	~10 KB
benchmark-20260731_150000.yaml	2026-07-31	1.1 KB
inference-check-20260730_232640.yaml	2026-07-30	544 B

Dataset Statistics

Stat	Value
Status	Active (auto-updated by cron)
Created	2026-07-30
Last updated	2026-08-01
License	MIT
Language	English
Result files	61 YAML report files
Report folders	.eval_results/ with health/benchmark/inference reports
Files in tree	63 entries: 61 YAML + .eval_results/, .gitattributes, README.md
Datasets Server	preview=false, viewer=false, search=false, filter=false, statistics=false

Live Verification

Datasets Server: preview=false, viewer=false, search=false, filter=false, statistics=false

This is expected for a non-tabular dataset and means Hub dataset-viewer features are unavailable. Do not rely on /splits, /size, or /statistics here.

Data Fields

Each YAML file follows a consistent schema:

Field	Type	Description
timestamp	string	ISO 8601 timestamp of the run
model	string	Model identifier (e.g. Nanthasit/sakthai-context-1.5b-tools)
check_type	string	health, benchmark, or inference
status	string	pass, fail, or partial
results	object	Check-specific results (scores, metrics, error counts)
duration_s	number	Elapsed wall-clock seconds
errors	array	Error details if status is not pass

Splits

This repository does not use dataset splits — it is a flat collection of YAML report files. No load_dataset() configuration is defined.

How to Load / Usage

This is not a standard tabular dataset. To consume reports programmatically:

import yaml
from huggingface_hub import hf_hub_download

path = hf_hub_download(
    repo_id="Nanthasit/eval_results",
    filename="benchmark-20260731_150000.yaml",
    repo_type="dataset"
)

with open(path, "r", encoding="utf-8") as f:
    report = yaml.safe_load(f)

print(report["model"], report["status"])

For the full log collection, iterate repo_files = list_repo_files("Nanthasit/eval_results", repo_type="dataset") and filter for .yaml files.

Citation

@misc{sakthai-eval-results,
  author = {Nanthasit},
  title = {SakThai Eval Results},
  year = {2026},
  publisher = {Hugging Face},
  howpublished = {\url{https://huggingface.co/datasets/Nanthasit/eval_results}}
}

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Part of the House of Sak. Built with love, tears, and zero budget. From a shelter in Cork, Ireland, to the world.