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17Lab/
qwen7b-dpo-s42base-dposeed-s42

Name: qwen7b-dpo-s42base-dposeed-s42
Availability: InStock

17Lab/qwen7b-full-sft-s42

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qwen7b_dpo_from_sft_s42base_s42

This model is a fine-tuned version of 17Lab/qwen7b-full-sft-s42 on the assimilation_dpo_v1 dataset. It achieves the following results on the evaluation set:

Loss: 0.0338
Rewards/chosen: 0.3783
Rewards/rejected: -5.3339
Rewards/accuracies: 1.0
Rewards/margins: 5.7122
Logps/chosen: -7.4223
Logps/rejected: -67.4563
Logits/chosen: -2.4565
Logits/rejected: -2.4412

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: 2
seed: 42
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 2
total_train_batch_size: 16
total_eval_batch_size: 4
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
0.0380	0.5025	50	0.0502	0.3352	-4.7318	1.0	5.0671	-7.8535	-61.4357	-2.4644	-2.4486
0.0439	1.0	100	0.0338	0.3783	-5.3339	1.0	5.7122	-7.4223	-67.4563	-2.4565	-2.4412

Framework versions

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

17Lab/qwen7b-dpo-s42base-dposeed-s42

qwen7b_dpo_from_sft_s42base_s42

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

17Lab/
qwen7b-dpo-s42base-dposeed-s42