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: 0.5042
Rewards/chosen: -1.0500
Rewards/rejected: -2.0480
Rewards/accuracies: 0.7539
Rewards/margins: 0.9980
Logps/rejected: -468.1450
Logps/chosen: -368.4135
Logits/rejected: 2.3821
Logits/chosen: 1.6141

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: 8
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: 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
0.5723	0.21	100	0.5851	-0.4097	-0.8752	0.7031	0.4655	-350.8695	-304.3812	-2.3494	-2.4070
0.5084	0.42	200	0.5251	-0.9116	-1.7472	0.7422	0.8355	-438.0663	-354.5790	1.3918	0.9248
0.5059	0.63	300	0.5130	-0.8646	-1.7542	0.75	0.8896	-438.7735	-349.8758	2.0331	1.2558
0.4853	0.84	400	0.5050	-1.0929	-2.1085	0.7539	1.0156	-474.1963	-372.7067	2.5922	1.8194

Framework versions

Transformers 4.36.2
Pytorch 2.1.2+cu121
Datasets 2.14.6
Tokenizers 0.15.0

RichardErkhov/alignment-handbook_-_zephyr-7b-dpo-full-4bits

Original model description:

zephyr-7b-dpo-full

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RichardErkhov/
alignment-handbook_-_zephyr-7b-dpo-full-4bits