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--- |
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license: apache-2.0 |
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base_model: hZzy/qwen2.5-0.5b-sft-news-IFT |
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tags: |
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- alignment-handbook |
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- ndcg |
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- trl |
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- expo |
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- generated_from_trainer |
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- trl |
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- expo |
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- generated_from_trainer |
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datasets: |
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- hZzy/train_pairwise_weighted |
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model-index: |
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- name: qwen2.5-0.5b-expo-L1EXPO-noES-0.1 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/zhiyuzha-university-of-florida/huggingface/runs/uh50oig6) |
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# qwen2.5-0.5b-expo-L1EXPO-noES-0.1 |
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This model is a fine-tuned version of [hZzy/qwen2.5-0.5b-sft-news-IFT](https://huggingface.co/hZzy/qwen2.5-0.5b-sft-news-IFT) on the hZzy/train_pairwise_weighted dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1381 |
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- Logps: -85.9802 |
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- Logits: -1.2306 |
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- Objective: 0.1370 |
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- Dpo Loss: 0.6974 |
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- Regularize: 0.1370 |
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- Ranking Simple: 0.5243 |
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- Ranking Idealized: 0.6025 |
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- Ranking Idealized Expo: 0.5233 |
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- Wo Beta: 15.6347 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 3 |
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- gradient_accumulation_steps: 12 |
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- total_train_batch_size: 144 |
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- total_eval_batch_size: 12 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Logps | Logits | Objective | Dpo Loss | Regularize | Ranking Simple | Ranking Idealized | Ranking Idealized Expo | Wo Beta | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|:-------:| |
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| 0.0351 | 0.1417 | 50 | 0.0221 | -91.2329 | -1.3917 | 0.0224 | 0.6927 | 0.0224 | 0.5212 | 0.6025 | 0.5233 | 16.2217 | |
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| 0.0877 | 0.2834 | 100 | 0.0433 | -88.6602 | -1.3863 | 0.0447 | 0.6922 | 0.0447 | 0.5238 | 0.6025 | 0.5233 | 16.1682 | |
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| 0.1323 | 0.4251 | 150 | 0.0768 | -90.4377 | -1.3054 | 0.0764 | 0.6956 | 0.0764 | 0.5223 | 0.6025 | 0.5233 | 16.0034 | |
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| 0.1427 | 0.5668 | 200 | 0.1032 | -88.3433 | -1.3124 | 0.1017 | 0.6959 | 0.1017 | 0.5223 | 0.6025 | 0.5233 | 15.9928 | |
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| 0.1451 | 0.7085 | 250 | 0.1178 | -88.0698 | -1.2854 | 0.1185 | 0.6950 | 0.1185 | 0.5274 | 0.6025 | 0.5233 | 15.7878 | |
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| 0.1305 | 0.8503 | 300 | 0.1247 | -86.3312 | -1.2863 | 0.1252 | 0.6961 | 0.1252 | 0.5280 | 0.6025 | 0.5233 | 15.7668 | |
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| 0.1407 | 0.9920 | 350 | 0.1314 | -86.4501 | -1.2757 | 0.1310 | 0.6976 | 0.1310 | 0.5223 | 0.6025 | 0.5233 | 15.6570 | |
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| 0.1245 | 1.1337 | 400 | 0.1399 | -86.2849 | -1.2418 | 0.1390 | 0.6980 | 0.1390 | 0.5259 | 0.6025 | 0.5233 | 15.6147 | |
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| 0.1163 | 1.2754 | 450 | 0.1421 | -85.4828 | -1.2307 | 0.1421 | 0.6985 | 0.1421 | 0.5274 | 0.6025 | 0.5233 | 15.6128 | |
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| 0.1071 | 1.4171 | 500 | 0.1382 | -87.2673 | -1.2270 | 0.1376 | 0.6980 | 0.1376 | 0.5285 | 0.6025 | 0.5233 | 15.6445 | |
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| 0.1045 | 1.5588 | 550 | 0.1428 | -87.0776 | -1.2327 | 0.1426 | 0.6977 | 0.1426 | 0.5254 | 0.6025 | 0.5233 | 15.5807 | |
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| 0.0866 | 1.7005 | 600 | 0.1424 | -85.1926 | -1.2196 | 0.1408 | 0.6965 | 0.1408 | 0.5269 | 0.6025 | 0.5233 | 15.6603 | |
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| 0.0847 | 1.8422 | 650 | 0.1380 | -86.1129 | -1.2229 | 0.1356 | 0.6974 | 0.1356 | 0.5243 | 0.6025 | 0.5233 | 15.6660 | |
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| 0.071 | 1.9839 | 700 | 0.1420 | -85.2496 | -1.2208 | 0.1405 | 0.6980 | 0.1405 | 0.5254 | 0.6025 | 0.5233 | 15.6109 | |
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| 0.0546 | 2.1256 | 750 | 0.1423 | -85.4691 | -1.2233 | 0.1407 | 0.6980 | 0.1407 | 0.5259 | 0.6025 | 0.5233 | 15.6480 | |
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| 0.0531 | 2.2674 | 800 | 0.1386 | -86.1368 | -1.2206 | 0.1371 | 0.6981 | 0.1371 | 0.5243 | 0.6025 | 0.5233 | 15.6234 | |
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| 0.0444 | 2.4091 | 850 | 0.1395 | -86.0362 | -1.2271 | 0.1382 | 0.6980 | 0.1382 | 0.5238 | 0.6025 | 0.5233 | 15.6472 | |
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| 0.0438 | 2.5508 | 900 | 0.1387 | -85.8840 | -1.2296 | 0.1374 | 0.6975 | 0.1374 | 0.5238 | 0.6025 | 0.5233 | 15.6345 | |
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| 0.0384 | 2.6925 | 950 | 0.1380 | -85.9590 | -1.2285 | 0.1368 | 0.6975 | 0.1368 | 0.5238 | 0.6025 | 0.5233 | 15.6425 | |
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| 0.0375 | 2.8342 | 1000 | 0.1380 | -85.9976 | -1.2305 | 0.1369 | 0.6974 | 0.1369 | 0.5243 | 0.6025 | 0.5233 | 15.6355 | |
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| 0.0397 | 2.9759 | 1050 | 0.1381 | -85.9802 | -1.2306 | 0.1370 | 0.6974 | 0.1370 | 0.5243 | 0.6025 | 0.5233 | 15.6347 | |
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### Framework versions |
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- Transformers 4.42.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.19.1 |
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