InternLM2-SFT-SCDPO
This model is a fine-tuned version of the InternLM2-20B model using SFT and SCDPO.
It achieves the following results on the evaluation set:
- Loss: 0.2572
- Rewards/chosen: 0.7366
- Rewards/rejected: -2.9817
- Rewards/accuracies: 0.8929
- Rewards/margins: 3.7183
- Logps/rejected: -155.1884
- Logps/chosen: -92.5904
- Logits/rejected: -2.3032
- Logits/chosen: -2.4880
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
| gsm8k | math | ape | cmath | mgsm_zh |
|---|
| InternLM2-SFT | 86.4 | 55.8 | 77.1 | 88.4 | 74.8 |
| InternLM2-SFT-DPO | 87 | 57.6 | 78.7 | 89.9 | 76 |
| InternLM2-SFT-DPO (data-equal) | 88.2 | 57.5 | 78.8 | 89.3 | 76 |
| InternLM2-SFT-SCDPO | 88.5 | 58.1 | 79.3 | 90.3 | 80.4 |
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1.5e-07
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 16
- total_train_batch_size: 32
- total_eval_batch_size: 64
- 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
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2
