dmis-lab/meditron-7b-olaph

meditron-7b-wo-kqa_golden-iter-dpo-step2

This model is a fine-tuned version of Minbyul/meditron-7b-wo-kqa_golden-iter-sft-step1 on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

• Loss: 0.6808
• Rewards/chosen: 0.0082
• Rewards/rejected: 0.0077
• Rewards/accuracies: 0.5625
• Rewards/margins: 0.0005
• Logps/rejected: -631.7355
• Logps/chosen: -407.7206
• Logits/rejected: -1.1718
• Logits/chosen: -1.2239

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