OLAPH
Collection
This collection hosts models introduced in OLAPH: Improving Factuality in Biomedical Long-form Question Answering.
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7 items
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Updated
selfbiorag-7b-wo-kqa_golden-iter-dpo-step4-filtered
This model is a fine-tuned version of Minbyul/selfbiorag-7b-wo-kqa_golden-iter-dpo-step3-filtered on the HuggingFace MedLFQA (without kqa_golden) dataset. It achieves the following results on the evaluation set:
- Loss: 0.6766
- Rewards/chosen: -0.0828
- Rewards/rejected: -0.1144
- Rewards/accuracies: 0.6319
- Rewards/margins: 0.0316
- Logps/rejected: -98.9601
- Logps/chosen: -79.1920
- Logits/rejected: -1.2073
- Logits/chosen: -1.1930
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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: 1
Training results
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2
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Model tree for dmis-lab/self-biorag-7b-olaph
Base model
dmis-lab/selfbiorag_7b