Release Gooya RizehPizeh v2 trainable checkpoint
Browse files- LICENSE +21 -0
- README.md +97 -0
- checkpoint/gooya-rizehpizeh-v2-step50000-val_mel0.3951.ckpt +3 -0
- config/negara-phoneme-id-map.json +498 -0
- release-manifest.json +53 -0
- training/alignment-report.json +48 -0
- training/base-onnx-roundtrip-parity.json +256 -0
- training/checkpoint-recovery-report.json +3479 -0
- training/train_rizeh_full_100k.sh +82 -0
LICENSE
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MIT License
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Copyright (c) 2026 Reza2kn
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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README.md
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---
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language:
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- fa
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license: mit
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pipeline_tag: text-to-speech
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base_model: Reza2kn/Gooya-RizehPizeh-v1.5
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library_name: piper
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model_type: text-to-speech
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tags:
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- audio
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- text-to-speech
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- piper
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- vits
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- persian
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- farsi
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- negara
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pretty_name: Gooya RizehPizeh v2
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---
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# Gooya RizehPizeh v2
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Persian (Farsi) single-speaker Piper/VITS2 voice fine-tuned on approved Gemini TTS Wikipedia audio. The model uses a case-sensitive Negara-style phonetic/Finglish frontend and produces 22,050 Hz mono audio.
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## Selected checkpoint
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This release selects the checkpoint at **global step 50,000** (`val_mel = 0.3951`). Training continued to 100,000 global steps, but later validation was worse, so the terminal state is intentionally not promoted.
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- Generator parameters: approximately 23.7M
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- Full trainable checkpoint: `checkpoint/gooya-rizehpizeh-v2-step50000-val_mel0.3951.ckpt`
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- Checkpoint SHA-256: `0c2d22718894e20fb6361c7bf2d75ee54d61db3a167983ce5d843ff6ed438938`
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- Sample rate: 22,050 Hz
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- Speakers: 1
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- Phoneme type: `text`
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- Symbol inventory: 256 IDs
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## Model lineage
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The original v1.5 production ONNX did not have a matching resumable checkpoint. A trainable hybrid checkpoint was reconstructed by copying all 350 inference-time generator tensors from the production ONNX into a compatible Mana Piper training checkpoint. Training-only branches absent from ONNX came from that Mana template.
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Before fine-tuning, a fresh ONNX round-trip matched the production model on 19/19 deterministic test rows:
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- Worst maximum absolute error: `1.0348856449127197e-05`
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- Minimum SNR: `110.0768 dB`
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- Minimum correlation: `0.999999999995`
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The complete recovery and parity receipts are under `training/`.
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## Fine-tuning data
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The parent corpus came from approved rows in [`Reza2kn/Wikipedia-FA-EN-DeepSeek-V4-Flash-0731`](https://huggingface.co/datasets/Reza2kn/Wikipedia-FA-EN-DeepSeek-V4-Flash-0731).
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- Requested parent clips: 4,186 (`3,517` train, `669` sealed eval)
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- Successfully aligned parents: 4,116
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- Rejected during alignment: 70
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- Materialized segments: 30,965
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- Training segments consumed: 26,053
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- Sealed eval segments, not consumed by training: 4,912
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- Total materialized duration: 68.9853 hours
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- Segment duration: mean `8.0203s`, min `0.6307s`, max `21.6656s`
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Audio timing came from AvaSanj v1 CTC forced alignment. Training phoneme labels came from Negara v7.1. Parent-level train/eval boundaries were preserved.
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## Training
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- Precision: BF16 mixed precision
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- Generator learning rate: `1e-5`
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- Discriminator learning rate: `5e-6`
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- Batch size: 1
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- Selected validation metric: `val_mel`
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- Selected checkpoint: global step 50,000, `val_mel = 0.3951`
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The 100K run was resumed from a successful 2K signal checkpoint. The sealed 669-parent eval split was not used for checkpoint selection.
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## Inference and long-form use
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Input must already be case-sensitive Negara-compatible phonetic text. Example:
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```bash
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echo "zurxAneye vahdat yek makAne varzeSi dar Sahre borujerd ast." | \
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piper --model gooya-rizehpizeh-v2.onnx \
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--config gooya-rizehpizeh-v2.onnx.json \
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--output_file output.wav
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```
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For long-form narration, do not send an article as one model input. Split at semantic sentence/clause boundaries into substantial spans, synthesize each span independently, trim quiet waveform edges, and join with boundary-aware pauses. The final output duration can be arbitrarily long even though each model invocation remains bounded.
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## Limitations
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- Lower validation mel loss did not guarantee universally better pronunciation. Human listening found some words, including proper nouns, better at the earlier 2K checkpoint or the original v1.5 model.
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- G2P/Finglish quality remains the dominant source of pronunciation errors.
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- Very long single-pass phoneme sequences can collapse or omit content; use chunked synthesis.
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- Overly small chunks sound breathy and robotic. Prefer substantial semantic spans instead of fixed tiny fragments.
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- This release has not yet been promoted over v1.5 on Gouya.app.
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## License
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MIT. See `LICENSE`.
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checkpoint/gooya-rizehpizeh-v2-step50000-val_mel0.3951.ckpt
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version https://git-lfs.github.com/spec/v1
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oid sha256:0c2d22718894e20fb6361c7bf2d75ee54d61db3a167983ce5d843ff6ed438938
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size 845890322
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config/negara-phoneme-id-map.json
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training/base-onnx-roundtrip-parity.json
ADDED
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training/checkpoint-recovery-report.json
ADDED
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@@ -0,0 +1,3479 @@
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|
| 3435 |
+
"shape": [
|
| 3436 |
+
192
|
| 3437 |
+
],
|
| 3438 |
+
"storage": "direct",
|
| 3439 |
+
"target": "dp.convs.norms_2.1.beta",
|
| 3440 |
+
"transform": "identity"
|
| 3441 |
+
},
|
| 3442 |
+
{
|
| 3443 |
+
"initializer": "dp.convs.norms_2.2.gamma",
|
| 3444 |
+
"shape": [
|
| 3445 |
+
192
|
| 3446 |
+
],
|
| 3447 |
+
"storage": "direct",
|
| 3448 |
+
"target": "dp.convs.norms_2.2.gamma",
|
| 3449 |
+
"transform": "identity"
|
| 3450 |
+
},
|
| 3451 |
+
{
|
| 3452 |
+
"initializer": "dp.convs.norms_2.2.beta",
|
| 3453 |
+
"shape": [
|
| 3454 |
+
192
|
| 3455 |
+
],
|
| 3456 |
+
"storage": "direct",
|
| 3457 |
+
"target": "dp.convs.norms_2.2.beta",
|
| 3458 |
+
"transform": "identity"
|
| 3459 |
+
},
|
| 3460 |
+
{
|
| 3461 |
+
"initializer": "onnx::Exp_8793",
|
| 3462 |
+
"shape": [
|
| 3463 |
+
2,
|
| 3464 |
+
1
|
| 3465 |
+
],
|
| 3466 |
+
"storage": "direct",
|
| 3467 |
+
"target": "dp.flows.0.logs",
|
| 3468 |
+
"transform": "negate"
|
| 3469 |
+
}
|
| 3470 |
+
],
|
| 3471 |
+
"training_only_initialization": {
|
| 3472 |
+
"modules": [
|
| 3473 |
+
"model_g.enc_q",
|
| 3474 |
+
"model_g.dp training-only branches",
|
| 3475 |
+
"model_d"
|
| 3476 |
+
],
|
| 3477 |
+
"source": "Mana parent checkpoint"
|
| 3478 |
+
}
|
| 3479 |
+
}
|
training/train_rizeh_full_100k.sh
ADDED
|
@@ -0,0 +1,82 @@
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#!/usr/bin/env bash
|
| 2 |
+
set -euo pipefail
|
| 3 |
+
|
| 4 |
+
root=/home/rezo/piper-wikipedia-approved-20260830
|
| 5 |
+
data="${root}/data/aligned-full-v1"
|
| 6 |
+
signal_run="${root}/runs/rizeh-recovered-approved-signal-2000"
|
| 7 |
+
run="${root}/runs/rizeh-recovered-approved-full-100k"
|
| 8 |
+
resume_checkpoint="${signal_run}/lightning_logs/version_1/checkpoints/last.ckpt"
|
| 9 |
+
|
| 10 |
+
[[ -s "${resume_checkpoint}" ]]
|
| 11 |
+
[[ "$(jq -r .status "${data}/report.json")" == complete ]]
|
| 12 |
+
mkdir -p "${run}"
|
| 13 |
+
|
| 14 |
+
cd "${root}/src/piper1-gpl"
|
| 15 |
+
"${root}/venv/bin/python" -m piper.train fit \
|
| 16 |
+
--trainer.accelerator gpu \
|
| 17 |
+
--trainer.devices 1 \
|
| 18 |
+
--trainer.precision bf16-mixed \
|
| 19 |
+
--trainer.max_steps 100000 \
|
| 20 |
+
--trainer.num_sanity_val_steps 0 \
|
| 21 |
+
--trainer.val_check_interval 500 \
|
| 22 |
+
--trainer.limit_val_batches 25 \
|
| 23 |
+
--trainer.log_every_n_steps 10 \
|
| 24 |
+
--trainer.enable_progress_bar false \
|
| 25 |
+
--trainer.default_root_dir "${run}" \
|
| 26 |
+
--model.sample_rate 22050 \
|
| 27 |
+
--model.num_speakers 1 \
|
| 28 |
+
--model.warmstart_ckpt null \
|
| 29 |
+
--model.learning_rate 0.00001 \
|
| 30 |
+
--model.learning_rate_d 0.000005 \
|
| 31 |
+
--model.mos_metric null \
|
| 32 |
+
--data.voice_name gooya-rizehpizeh-wikipedia-kore-full-100k \
|
| 33 |
+
--data.csv_path "${data}/metadata-train.csv" \
|
| 34 |
+
--data.audio_dir / \
|
| 35 |
+
--data.cache_dir "${root}/cache/aligned-full-v1" \
|
| 36 |
+
--data.config_path "${signal_run}/model.onnx.json" \
|
| 37 |
+
--data.batch_size 1 \
|
| 38 |
+
--data.validation_split 0.01 \
|
| 39 |
+
--data.num_test_examples 0 \
|
| 40 |
+
--data.num_workers 2 \
|
| 41 |
+
--data.trim_silence false \
|
| 42 |
+
--data.phoneme_type text \
|
| 43 |
+
--data.dataset_type phoneme_ids \
|
| 44 |
+
--data.phonemes_path "${data}/negara-phoneme-id-map.json" \
|
| 45 |
+
--data.espeak_voice fa \
|
| 46 |
+
--data.num_symbols 256 \
|
| 47 |
+
--ckpt_path "${resume_checkpoint}"
|
| 48 |
+
|
| 49 |
+
last_checkpoint=$(find "${run}" -name last.ckpt -type f -printf '%T@ %p\n' | sort -nr | head -1 | cut -d' ' -f2-)
|
| 50 |
+
best_checkpoint=$("${root}/venv/bin/python" - "${run}" <<'PY'
|
| 51 |
+
import re
|
| 52 |
+
import sys
|
| 53 |
+
from pathlib import Path
|
| 54 |
+
|
| 55 |
+
run = Path(sys.argv[1])
|
| 56 |
+
candidates = []
|
| 57 |
+
for path in run.glob("lightning_logs/version_*/checkpoints/*val_mel=*.ckpt"):
|
| 58 |
+
match = re.search(r"val_mel=([0-9.]+)\.ckpt$", path.name)
|
| 59 |
+
if match:
|
| 60 |
+
candidates.append((float(match.group(1)), str(path)))
|
| 61 |
+
if not candidates:
|
| 62 |
+
raise SystemExit("No validation checkpoint found")
|
| 63 |
+
print(min(candidates)[1])
|
| 64 |
+
PY
|
| 65 |
+
)
|
| 66 |
+
[[ -s "${last_checkpoint}" ]]
|
| 67 |
+
[[ -s "${best_checkpoint}" ]]
|
| 68 |
+
|
| 69 |
+
"${root}/venv/bin/python" -m piper.train.export_onnx \
|
| 70 |
+
--checkpoint "${best_checkpoint}" \
|
| 71 |
+
--output-file "${run}/model-best.onnx"
|
| 72 |
+
|
| 73 |
+
printf '%s\n' 'zurxAneye vahdat yek makAne varzeSi dar Sahre borujerd ast.' | \
|
| 74 |
+
"${root}/venv/bin/python" -m piper \
|
| 75 |
+
-m "${run}/model-best.onnx" \
|
| 76 |
+
-f "${run}/zurxane-full-100k-best.wav" \
|
| 77 |
+
--length-scale 1.15
|
| 78 |
+
|
| 79 |
+
sha256sum "${last_checkpoint}" "${best_checkpoint}" "${run}/model-best.onnx" \
|
| 80 |
+
"${run}/model-best.onnx.json" "${run}/zurxane-full-100k-best.wav" \
|
| 81 |
+
> "${run}/sha256sums.txt"
|
| 82 |
+
echo "full_complete_utc=$(date -u +%FT%TZ) last=${last_checkpoint} best=${best_checkpoint}"
|