This model is a fine-tuned version of JunxiongWang/llama3_mamba_0_5_sft on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

Loss: 0.6148
Rewards/chosen: -3.5162
Rewards/rejected: -5.9459
Rewards/accuracies: 0.7812
Rewards/margins: 2.4297
Logps/rejected: -326.2092
Logps/chosen: -294.7739
Logits/rejected: -1.2401
Logits/chosen: -1.1951

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: 4
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 8
total_train_batch_size: 32
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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.2025	1.0466	2000	0.5107	-1.2087	-2.7320	0.7930	1.5234	-294.0709	-271.6987	-1.0884	-1.0320
0.0265	2.0931	4000	0.6148	-3.5162	-5.9459	0.7812	2.4297	-326.2092	-294.7739	-1.2401	-1.1951

Framework versions

Transformers 4.41.2
Pytorch 2.1.0+cu118
Datasets 2.20.0
Tokenizers 0.19.1