metadata

license: apache-2.0
base_model: Minbyul/mistral-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: mistral-7b-dpo-full-sft-wo-kqa_silver_wogold
    results: []

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

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

Loss: 0.0530
Rewards/chosen: -2.4760
Rewards/rejected: -21.0723
Rewards/accuracies: 0.9700
Rewards/margins: 18.5963
Logps/rejected: -2709.2131
Logps/chosen: -407.7003
Logits/rejected: -2.0225
Logits/chosen: -2.2276

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
0.2735	0.32	100	0.0529	-1.3592	-8.1857	0.9700	6.8265	-1420.5509	-296.0260	-2.7457	-2.5375
0.1321	0.63	200	0.0507	-2.0405	-16.8511	0.9600	14.8106	-2287.0967	-364.1557	-2.2518	-2.3349
0.117	0.95	300	0.0531	-2.4855	-21.1345	0.9700	18.6490	-2715.4331	-408.6504	-2.0210	-2.2273

Framework versions

Transformers 4.39.0.dev0
Pytorch 2.1.2
Datasets 2.14.6
Tokenizers 0.15.2