llama3-8b-base-dpo – AI Model by yangzhao02 | AlphaNeural AI

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yangzhao02/
llama3-8b-base-dpo

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text-generation

generated_from_trainer

autotrain_compatible

text-generation-inference

endpoints_compatible

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llama3-8b-base-dpo-120

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4893
Rewards/chosen: -0.5883
Rewards/rejected: -1.3409
Rewards/accuracies: 0.6905
Rewards/margins: 0.7525
Logps/rejected: -293.5897
Logps/chosen: -331.5697
Logits/rejected: 0.4485
Logits/chosen: 0.2338

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: 2
seed: 42
distributed_type: multi-GPU
num_devices: 24
gradient_accumulation_steps: 5
total_train_batch_size: 120
total_eval_batch_size: 48
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
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.467	0.4906	250	0.4987	-0.6034	-1.2547	0.7262	0.6512	-291.8655	-331.8713	0.4838	0.2542
0.4536	0.9812	500	0.4893	-0.5883	-1.3409	0.6905	0.7525	-293.5897	-331.5697	0.4485	0.2338

Framework versions

Transformers 4.42.0
Pytorch 2.2.2+cu121
Datasets 2.19.1
Tokenizers 0.19.1