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chchen/
Llama-3.1-8B-Instruct-SAA-100

Name: Llama-3.1-8B-Instruct-SAA-100
Availability: InStock

generated_from_trainer

meta-llama/Llama-3.1-8B-Instruct

adapter

llama3.1

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Llama-3.1-8B-Instruct-SAA-100

This model is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct on the bct_non_cot_dpo_100 dataset. It achieves the following results on the evaluation set:

Loss: 1.6738
Rewards/chosen: -0.1622
Rewards/rejected: -0.2212
Rewards/accuracies: 0.8000
Rewards/margins: 0.0590
Logps/rejected: -2.2122
Logps/chosen: -1.6219
Logits/rejected: -0.5028
Logits/chosen: -0.3970
Sft Loss: 0.2269
Odds Ratio Loss: 14.4681

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: 2
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10.0

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen	Sft Loss	Odds Ratio Loss
1.3868	8.8889	50	1.6738	-0.1622	-0.2212	0.8000	0.0590	-2.2122	-1.6219	-0.5028	-0.3970	0.2269	14.4681

Framework versions

PEFT 0.12.0
Transformers 4.45.2
Pytorch 2.3.0
Datasets 2.19.0
Tokenizers 0.20.0

chchen/Llama-3.1-8B-Instruct-SAA-100

Llama-3.1-8B-Instruct-SAA-100

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

chchen/
Llama-3.1-8B-Instruct-SAA-100