biomistral-7b-dpo-full-wo-kqa_golden-ep3

This model is a fine-tuned version of BioMistral/BioMistral-7B on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

• Loss: 0.4863
• Rewards/chosen: -0.4536
• Rewards/rejected: -1.6547
• Rewards/accuracies: 0.7773
• Rewards/margins: 1.2011
• Logps/rejected: -414.8132
• Logps/chosen: -197.4666
• Logits/rejected: 1.1489
• Logits/chosen: -1.2246

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

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.3773	0.33	100	0.5260	-0.1419	-0.7006	0.8242	0.5587	-319.4027	-166.2970	0.1795	-1.6741
0.2183	0.67	200	0.4886	-0.4036	-1.5266	0.7891	1.1229	-402.0057	-192.4719	1.1365	-1.2204

Framework versions

• Transformers 4.39.0.dev0
• Pytorch 2.1.2
• Datasets 2.14.6
• Tokenizers 0.15.2