genv3pair1NoGT_1.5B_cdpo_ebs32_lr5e-07_beta0.0_epoch8.0_42
This model is a fine-tuned version of Qwen/Qwen2.5-1.5B-Instruct on the YuchenLi01/MATH_Qwen2.5-1.5BInstruct_DPO_MoreUniqueResponseNoGTv3pair1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6931
- Rewards/chosen: 0.0
- Rewards/rejected: 0.0
- Rewards/accuracies: 0.0
- Rewards/margins: 0.0
- Logps/rejected: -41.6977
- Logps/chosen: -30.0700
- Logits/rejected: -2.2294
- Logits/chosen: -2.3763
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-07
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 8.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6931 | 0.1117 | 20 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 0.2235 | 40 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 0.3352 | 60 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 0.4469 | 80 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 0.5587 | 100 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 0.6704 | 120 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 0.7821 | 140 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 0.8939 | 160 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 1.0056 | 180 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 1.1173 | 200 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 1.2291 | 220 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 1.3408 | 240 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 1.4525 | 260 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 1.5642 | 280 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 1.6760 | 300 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 1.7877 | 320 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 1.8994 | 340 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 2.0112 | 360 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 2.1229 | 380 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 2.2346 | 400 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 2.3464 | 420 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 2.4581 | 440 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 2.5698 | 460 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 2.6816 | 480 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 2.7933 | 500 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 2.9050 | 520 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 3.0168 | 540 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 3.1285 | 560 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 3.2402 | 580 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 3.3520 | 600 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 3.4637 | 620 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 3.5754 | 640 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 3.6872 | 660 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 3.7989 | 680 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 3.9106 | 700 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 4.0223 | 720 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 4.1341 | 740 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 4.2458 | 760 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 4.3575 | 780 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 4.4693 | 800 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 4.5810 | 820 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 4.6927 | 840 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 4.8045 | 860 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 4.9162 | 880 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 5.0279 | 900 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 5.1397 | 920 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 5.2514 | 940 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 5.3631 | 960 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 5.4749 | 980 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 5.5866 | 1000 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 5.6983 | 1020 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 5.8101 | 1040 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 5.9218 | 1060 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 6.0335 | 1080 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 6.1453 | 1100 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 6.2570 | 1120 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 6.3687 | 1140 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 6.4804 | 1160 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 6.5922 | 1180 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 6.7039 | 1200 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 6.8156 | 1220 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 6.9274 | 1240 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 7.0391 | 1260 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 7.1508 | 1280 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 7.2626 | 1300 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 7.3743 | 1320 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 7.4860 | 1340 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 7.5978 | 1360 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 7.7095 | 1380 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 7.8212 | 1400 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
| 0.6931 | 7.9330 | 1420 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -41.6977 | -30.0700 | -2.2294 | -2.3763 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.5.0
- Tokenizers 0.20.3
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