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This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.6004
• Eval/rewards/chosen: 0.0713
• Eval/logps/chosen: -174.6075
• Eval/rewards/rejected: 0.0986
• Eval/logps/rejected: -217.2799
• Eval/rewards/margins: -0.0273
• Eval/kl: 0.7783

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: 1e-05
• train_batch_size: 1
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.5651	0.9677	15	0.6026	0.1513
0.5618	2.0	31	0.5999	0.3742
0.5484	2.9677	46	0.6006	0.6711
0.5466	4.0	62	0.6003	0.8158
0.6017	4.8387	75	0.6004	0.7783

Framework versions

• PEFT 0.11.1
• Transformers 4.42.2
• Pytorch 2.2.0
• Datasets 2.20.0
• Tokenizers 0.19.1