This model is a fine-tuned version of oxford-llms/llama3-1-ox-llms-8b-sft-full on the argilla/dpo-mix-7k dataset. It achieves the following results on the evaluation set:

Loss: 0.4831
Rewards/chosen: -0.2543
Rewards/rejected: -1.0940
Rewards/accuracies: 0.7708
Rewards/margins: 0.8397
Logps/rejected: -340.3136
Logps/chosen: -325.1967
Logits/rejected: -1.3101
Logits/chosen: -1.3085

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: 4
seed: 42
distributed_type: multi-GPU
num_devices: 8
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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.528	0.9479	100	0.5267	-0.0255	-0.6055	0.7604	0.5800	-330.5430	-320.6201	-1.3169	-1.3159
0.3731	1.8957	200	0.4821	-0.2481	-1.0900	0.7604	0.8419	-340.2323	-325.0733	-1.3099	-1.3082

Framework versions

Transformers 4.45.1
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.20.3

oxford-llms/llama3-1-ox-llms-8b-dpo-full

llama3-1-ox-llms-8b-dpo-full

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

oxford-llms/
llama3-1-ox-llms-8b-dpo-full