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
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