51 lines
1.3 KiB
Markdown
51 lines
1.3 KiB
Markdown
---
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license: apache-2.0
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- qwen3
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- reinforcement-learning
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- grpo
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---
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# qwen3-8b-material-grpo
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Fine-tuned from `Qwen/Qwen3-8B` with GRPO on the `material` split.
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## Validation Performance
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Metric: `val-aux/sciknoweval/reward/mean@16` from 10-step validation logs.
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| best mean@16 | best step | final mean@16 | final step |
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|---:|---:|---:|---:|
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| 78.06% | 100 | 78.06% | 100 |
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| step | mean@16 |
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|---:|---:|
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| 10 | 68.95% |
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| 20 | 70.68% |
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| 30 | 74.73% |
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| 40 | 75.47% |
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| 50 | 76.33% |
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| 60 | 77.86% |
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| 70 | 76.99% |
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| 80 | 77.39% |
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| 90 | 77.99% |
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| 100 | 78.06% |
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Files included with this repo:
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- `metrics.json`: parsed validation summary
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- `eval_mean16.csv`: step-level validation curve data
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- `eval_mean16.png`: validation curve plot
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Important: the uploaded weights are the final `global_step_100/actor` checkpoint. If `best step` is earlier than 100, the best validation point is reported for tracking, but the corresponding actor weights may not be retained locally.
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Checkpoint source:
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`/mnt/mole/SDPO/L2T/checkpoints/datasets/sciknoweval/material/qwen3gen-material-GRPO-Qwen-Qwen3-8B-mbs8-train64-rollout8-lr1e-6-vllm0.8`
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W&B run: `run-20260701_005129-3hqobzfs`
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This upload uses `global_step_100/actor` converted from VERL FSDP shards to Hugging Face format.
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