uf-rlced-conifer_tulu-2-7b-dpo-full

This model is a fine-tuned version of allenai/tulu-2-7b on the data/uf_rlced_conifer dataset. It achieves the following results on the evaluation set:

• Loss: 0.3316
• Rewards/chosen: -2.6774
• Rewards/rejected: -5.0456
• Rewards/accuracies: 0.8383
• Rewards/margins: 2.3682
• Logps/rejected: -989.8275
• Logps/chosen: -729.1251
• Logits/rejected: -0.3176
• Logits/chosen: -0.4437

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: 8
• gradient_accumulation_steps: 4
• total_train_batch_size: 256
• total_eval_batch_size: 64
• 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 4.44.1
• Pytorch 2.1.2+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1