This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct-1M on the yangzhao02/ListUltraFeedback dataset. It achieves the following results on the evaluation set:

Loss: 6.8770
Logps: -731.7206
Logits: -0.5560
Rank Correct Batch: 16.5650
Rank Pair Batch: 28.0
Rank Accuracy Batch: 0.5916

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: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 16
total_train_batch_size: 128
total_eval_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	Logps	Logits	Rank Correct Batch	Rank Pair Batch	Rank Accuracy Batch
7.253	0.2672	125	7.2435	-631.0031	-0.5630	16.0366	28.0	0.5727
7.0458	0.5344	250	6.9577	-711.2150	-0.5474	16.4350	28.0	0.5870
6.879	0.8016	375	6.8770	-731.7206	-0.5560	16.5650	28.0	0.5916

Framework versions

Transformers 4.45.1
Pytorch 2.6.0+cu126
Datasets 2.19.1
Tokenizers 0.20.3

yangzhao02/qwen2.5-7b-dpo-list_mle

qwen2.5-7b-dpo-list_mle

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

yangzhao02/
qwen2.5-7b-dpo-list_mle