metadata

base_model: Minbyul/llama2-7b-wo-kqa_silver_wogold-sft
tags:
  - alignment-handbook
  - trl
  - dpo
  - generated_from_trainer
  - trl
  - dpo
  - generated_from_trainer
datasets:
  - HuggingFaceH4/ultrafeedback_binarized
model-index:
  - name: llama2-7b-dpo-full-sft-wo-kqa_silver_wogold
    results: []

llama2-7b-dpo-full-sft-wo-kqa_silver_wogold

This model is a fine-tuned version of Minbyul/llama2-7b-wo-kqa_silver_wogold-sft on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

Loss: 0.4452
Rewards/chosen: -0.0311
Rewards/rejected: -1.1476
Rewards/accuracies: 0.9418
Rewards/margins: 1.1165
Logps/rejected: -714.4130
Logps/chosen: -108.8849
Logits/rejected: -0.4047
Logits/chosen: -0.9197

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
0.2705	0.93	100	0.4456	-0.0307	-1.1443	0.9418	1.1136	-714.0911	-108.8464	-0.4045	-0.9202

Framework versions

Transformers 4.39.0.dev0
Pytorch 2.1.2
Datasets 2.14.6
Tokenizers 0.15.2