deepseek-8b-orpo-lora
This model is a fine-tuned version of deepseek-ai/deepseek-math-7b-base on the zfz1/my_preference_gsm8k_deepseek dataset. It achieves the following results on the evaluation set:
- Loss: 0.6818
- Rewards/chosen: -0.0338
- Rewards/rejected: -0.0840
- Rewards/accuracies: 0.8088
- Rewards/margins: 0.0502
- Logps/rejected: -0.8398
- Logps/chosen: -0.3377
- Logits/rejected: 34.4233
- Logits/chosen: 35.5254
- Nll Loss: 0.6414
- Log Odds Ratio: -0.4212
- Log Odds Chosen: 1.0634
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 43
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- 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
Training results
Framework versions
- PEFT 0.11.1
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for zfz1/deepseek-8b-orpo-lora
Base model
deepseek-ai/deepseek-math-7b-base