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selfbiorag-7b-wo-kqa_golden-iter-dpo-step4-filtered – AI Model by Minbyul | AlphaNeural AI
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Minbyul
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selfbiorag-7b-wo-kqa_golden-iter-dpo-step4-filtered
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transformers
safetensors
llama
text-generation
alignment-handbook
trl
dpo
generated_from_trainer
HuggingFaceH4/ultrafeedback_binarized
Minbyul/selfbiorag-7b-wo-kqa_golden-iter-dpo-step3-filtered
finetune
autotrain_compatible
text-generation-inference
endpoints_compatible
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selfbiorag-7b-wo-kqa_golden-iter-dpo-step4-filtered
This model is a fine-tuned version of
Minbyul/selfbiorag-7b-wo-kqa_golden-iter-dpo-step3-filtered
on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
Loss: 0.6766
Rewards/chosen: -0.0828
Rewards/rejected: -0.1144
Rewards/accuracies: 0.6319
Rewards/margins: 0.0316
Logps/rejected: -98.9601
Logps/chosen: -79.1920
Logits/rejected: -1.2073
Logits/chosen: -1.1930
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: 8
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 2
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
Framework versions
Transformers 4.39.0.dev0
Pytorch 2.1.2
Datasets 2.14.6
Tokenizers 0.15.2
