This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

Loss: 0.8962
Rewards/chosen: 1.9939
Rewards/rejected: 0.7547
Rewards/accuracies: 0.3333
Rewards/margins: 1.2392
Logps/rejected: -80.3691
Logps/chosen: -72.4852
Logits/rejected: -2.5165
Logits/chosen: -2.5326

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: 6.25619875685306e-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: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.6244	1.0417	100	0.8359	1.9508	1.2167	0.3333	0.7341	-79.9043	-72.5286	-2.5408	-2.5561

Framework versions

Transformers 4.44.2
Pytorch 2.4.0
Datasets 2.21.0
Tokenizers 0.19.1

taicheng/zephyr-7b-align-scan-0.0-1.0-linear-2

zephyr-7b-align-scan-0.0-1.0-linear-2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

taicheng/
zephyr-7b-align-scan-0.0-1.0-linear-2