| # Phase 2: LoRA SFT on Erinome dataset |
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| **Date:** Mon Apr 27 03:22:08 UTC 2026 |
| **GPU:** RTX 4090 inst-35658834 vast.ai |
| **Cost:** ~$1/hr × 1.5h ≈ $1.50 |
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| ## Setup |
| - Base model: OpenMOSS-Team/MOSS-TTS-Nano-100M (227MB) |
| - Codec: OpenMOSS-Team/MOSS-Audio-Tokenizer-Nano (85MB) |
| - Dataset: marcosremar2/gemini-dataset-erinome (9995 wavs, 10000 texts, 4929 valid pairs) |
| - Train config: per_device_bs=8, grad_accum=4, global_bs=32, lr=5e-5 cosine, warmup=5%, 3 epochs (465 steps), bf16 |
| - Train time: 10min on RTX 4090 |
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| ## Train metrics |
| - Loss: 5.5 → 4.7 (decrease over 3 epochs) |
| - Steps: 465 |
| - Samples/sec: 26.47 |
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| ## Eval (50-prompt holdout) |
| - Whisper-base ASR, language=pt, fp16 |
| - WER computed via jiwer |
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| | Model | WER | N | |
| |---|---|---| |
| | Baseline | 0.5316 | 50 | |
| | SFT | 0.1537 | 50 | |
| | **Δ** | **-0.3779 (-71%)** | | |
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| ## Files |
| - Checkpoint: ./checkpoints/iaratts-sft-v1/checkpoint-last |
| - Eval prompts: /root/iaratts/eval_prompts.jsonl |
| - Eval audios: /root/iaratts/eval_out/{baseline,sft}/ |
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