dpo-selective-mixdata – AI Model by wxzhang | AlphaNeural AI

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wxzhang/
dpo-selective-mixdata

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text-generation

generated_from_trainer

autotrain_compatible

text-generation-inference

endpoints_compatible

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dpo-selective-mixdata

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5805
Rewards/chosen: -4.7292
Rewards/rejected: -5.2763
Rewards/accuracies: 0.6934
Rewards/margins: 0.5471
Logps/rejected: -654.5243
Logps/chosen: -590.7578
Logits/rejected: 6.2956
Logits/chosen: 6.4467

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: 4
gradient_accumulation_steps: 4
total_train_batch_size: 64
total_eval_batch_size: 32
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
0.5481	0.27	500	0.6089	-2.6822	-3.1236	0.6705	0.4414	-439.2521	-386.0565	3.9671	4.1604
0.5519	0.53	1000	0.5867	-4.2523	-4.7597	0.6894	0.5074	-602.8671	-543.0739	5.1974	5.3486
0.5597	0.8	1500	0.5821	-4.7906	-5.3218	0.6959	0.5311	-659.0733	-596.9037	6.4644	6.6294

Framework versions

Transformers 4.36.2
Pytorch 2.1.2
Datasets 2.14.6
Tokenizers 0.15.0