Step-Controlled DPO
Collection
Models and Datasets of Step-Controlled DPO.
•
6 items
•
Updated
•
2
Mistral-7B-Ours-SFT-SCDPO
This model is a fine-tuned version of MathGenie/Mistral-7B-Ours-SFT. It achieves the following results on the evaluation set:
- Loss: 0.1793
- Rewards/chosen: 0.2587
- Rewards/rejected: -7.0301
- Rewards/accuracies: 0.8947
- Rewards/margins: 7.2889
- Logps/rejected: -253.7773
- Logps/chosen: -80.3105
- Logits/rejected: -2.3417
- Logits/chosen: -2.3846
Model description
This is a model fine-tuned for mathematical problem-solving.
Intended uses & limitations
The model is intended for solving math problems.
Training and evaluation data
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-07
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.3963 | 0.21 | 100 | 0.3636 | 1.8634 | -0.1518 | 0.8816 | 2.0152 | -184.9944 | -64.2644 | -2.7112 | -2.7505 |
| 0.2849 | 0.43 | 200 | 0.2598 | 0.7706 | -3.7221 | 0.8816 | 4.4927 | -220.6974 | -75.1921 | -2.5067 | -2.5475 |
| 0.2496 | 0.64 | 300 | 0.2295 | 0.9323 | -4.2717 | 0.8684 | 5.2040 | -226.1934 | -73.5753 | -2.5080 | -2.5494 |
| 0.2331 | 0.86 | 400 | 0.2089 | 0.7871 | -4.8912 | 0.8684 | 5.6783 | -232.3884 | -75.0269 | -2.4967 | -2.5382 |
| 0.0874 | 1.07 | 500 | 0.1872 | 0.6345 | -5.7444 | 0.8816 | 6.3789 | -240.9202 | -76.5527 | -2.4323 | -2.4761 |
| 0.1217 | 1.28 | 600 | 0.1832 | 0.2282 | -6.6907 | 0.8684 | 6.9188 | -250.3827 | -80.6161 | -2.3741 | -2.4172 |
| 0.0966 | 1.5 | 700 | 0.1807 | 0.1849 | -7.0125 | 0.8816 | 7.1975 | -253.6012 | -81.0485 | -2.3503 | -2.3940 |
| 0.0755 | 1.71 | 800 | 0.1802 | 0.3224 | -6.9539 | 0.8947 | 7.2763 | -253.0150 | -79.6739 | -2.3437 | -2.3867 |
| 0.1177 | 1.93 | 900 | 0.1793 | 0.2587 | -7.0301 | 0.8947 | 7.2889 | -253.7773 | -80.3105 | -2.3417 | -2.3846 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2
- Downloads last month
- 13
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for MathGenie/Mistral-7B-Ours-SFT-SCDPO
Base model
MathGenie/Mistral-7B-Ours-SFT