This model is a fine-tuned version of data/norllm-ai-normistral-7b-sft-qlora on the hugodk-sch/aftonposten_title_prefs dataset. It achieves the following results on the evaluation set:

Loss: 0.9294
Rewards/chosen: -0.0900
Rewards/rejected: -0.1614
Rewards/accuracies: 0.6009
Rewards/margins: 0.0715
Logps/rejected: -35.5053
Logps/chosen: -31.7323
Logits/rejected: -2.8259
Logits/chosen: -2.8279

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
gradient_accumulation_steps: 2
total_train_batch_size: 8
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
0.9239	0.26	100	0.9661	-0.0010	-0.0351	0.6013	0.0342	-34.8738	-31.2872	-2.8027	-2.8055
0.8146	0.52	200	0.9363	-0.0747	-0.1389	0.6184	0.0641	-35.3925	-31.6561	-2.8206	-2.8233
0.7173	0.78	300	0.9279	-0.0837	-0.1567	0.6125	0.0730	-35.4817	-31.7010	-2.8247	-2.8267

Framework versions

PEFT 0.10.0
Transformers 4.39.0.dev0
Pytorch 2.1.2+cu121
Datasets 2.14.6
Tokenizers 0.15.1

hugodk-sch/norllm-ai-normistral-7b-align-scan

norllm-ai-normistral-7b-align-scan

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hugodk-sch/
norllm-ai-normistral-7b-align-scan