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skymizer/Llama2-7b-sft-chat-custom-template-dpo

sourceHugging Facellama2updated 2y agoView on Hugging Face
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Llama2-7b-sft-chat-custom-template-dpo

This model is a fine-tuned version of elichen3051/llama2-7b-sft-chat-no-template on the HuggingFaceH4/ultrafeedbackbinarized, the HuggingFaceH4/orcadpo_pairs and the HuggingFaceH4/cai-conversation-harmless datasets. It achieves the following results on the evaluation set:

  • —Loss: 0.4717
  • —Rewards/chosen: -1.6807
  • —Rewards/rejected: -3.1957
  • —Rewards/accuracies: 0.6345
  • —Rewards/margins: 1.5150
  • —Logps/rejected: -519.5196
  • —Logps/chosen: -379.2986
  • —Logits/rejected: -2.7275
  • —Logits/chosen: -2.7213

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
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —distributed_type: multi-GPU
  • —num_devices: 7
  • —gradientaccumulationsteps: 8
  • —totaltrainbatch_size: 448
  • —totalevalbatch_size: 56
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_ratio: 0.03
  • —num_epochs: 2

Training results

Training LossEpochStepValidation LossRewards/chosenRewards/rejectedRewards/accuraciesRewards/marginsLogps/rejectedLogps/chosenLogits/rejectedLogits/chosen
0.67270.2032430.6714-0.0530-0.09990.58710.0470-209.9431-216.5270-2.2167-2.2006
0.60560.4064860.6041-0.5876-0.88780.60230.3002-288.7347-269.9940-3.0277-3.0177
0.5730.60961290.5451-0.9286-1.60150.61740.6729-360.0960-304.0913-2.9301-2.9238
0.52390.81281720.5123-1.2863-2.23580.62880.9495-423.5324-339.8588-2.9884-2.9803
0.46681.01592150.4945-1.4994-2.63770.64391.1383-463.7195-361.1752-2.5910-2.5843
0.46071.21912580.4816-1.5810-2.88870.64021.3077-488.8177-369.3280-2.8026-2.7951
0.50681.42233010.4764-1.5805-3.00610.64021.4256-500.5590-369.2790-2.7586-2.7513
0.47241.62553440.4730-1.6832-3.17410.63831.4909-517.3631-379.5493-2.6296-2.6237
0.48361.82873870.4718-1.6795-3.19000.64201.5105-518.9514-379.1832-2.6434-2.6374

Framework versions

  • —Transformers 4.42.0.dev0
  • —Pytorch 2.3.1
  • —Datasets 2.19.2
  • —Tokenizers 0.19.1