qwen14b-dpo-rank256-s42 – AI Model by 17Lab | AlphaNeural AI

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qwen14b-dpo-rank256-s42

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text-generation

Qwen/Qwen2.5-14B

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qwen14b_dpo_from_sft_rank_s42

This model is a fine-tuned version of Qwen/Qwen2.5-14B on the assimilation_dpo_v1 dataset. It achieves the following results on the evaluation set:

Loss: 0.0272
Rewards/chosen: -0.1747
Rewards/rejected: -6.2640
Rewards/accuracies: 1.0
Rewards/margins: 6.0893
Logps/chosen: -5.2166
Logps/rejected: -80.8057
Logits/chosen: -1.5318
Logits/rejected: -1.5291

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: 2
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 16
total_train_batch_size: 64
total_eval_batch_size: 2
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 0.1
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/chosen	Logps/rejected	Logits/chosen	Logits/rejected
0.0329	1.0	25	0.0272	-0.1747	-6.2640	1.0	6.0893	-5.2166	-80.8057	-1.5318	-1.5291

Framework versions

PEFT 0.18.1
Transformers 5.6.0
Pytorch 2.7.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2