metadata

license: apache-2.0
library_name: peft
tags:
  - alignment-handbook
  - generated_from_trainer
  - trl
  - dpo
  - generated_from_trainer
datasets:
  - HuggingFaceH4/ultrafeedback_binarized
base_model: mistralai/Mistral-7B-v0.1
model-index:
  - name: zephyr-7b-dpo-qlora-fix
    results: []

zephyr-7b-dpo-qlora-fix

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

Loss: 0.5279
Rewards/chosen: -1.0268
Rewards/rejected: -1.8204
Rewards/accuracies: 0.7617
Rewards/margins: 0.7936
Logps/rejected: -429.5990
Logps/chosen: -349.1275
Logits/rejected: 1.1048
Logits/chosen: 1.1977

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-06
train_batch_size: 4
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 4
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
0.5985	0.21	100	0.6167	-0.6622	-0.9981	0.7031	0.3359	-347.3664	-312.6618	-2.0061	-1.9992
0.5302	0.42	200	0.5495	-0.8758	-1.5987	0.7461	0.7229	-407.4292	-334.0204	0.3116	0.4001
0.533	0.63	300	0.5384	-0.8142	-1.5157	0.7617	0.7016	-399.1313	-327.8605	0.5716	0.6809
0.518	0.84	400	0.5276	-1.0554	-1.8498	0.75	0.7944	-432.5438	-351.9892	1.1053	1.1955

Framework versions

PEFT 0.7.1
Transformers 4.36.2
Pytorch 2.1.2+cu121
Datasets 2.14.6
Tokenizers 0.15.1