LBK95's picture
End of training
d54a900 verified
metadata
library_name: peft
license: llama2
base_model: meta-llama/Llama-2-7b-hf
tags:
  - trl
  - dpo
  - generated_from_trainer
model-index:
  - name: Llama-2-7b-hf-DPO-LookAhead-0_TTree1.4_TT0.9_TP0.7_TE0.2_V7
    results: []

Llama-2-7b-hf-DPO-LookAhead-0_TTree1.4_TT0.9_TP0.7_TE0.2_V7

This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1519
  • Rewards/chosen: -2.8728
  • Rewards/rejected: -2.9359
  • Rewards/accuracies: 0.4000
  • Rewards/margins: 0.0631
  • Logps/rejected: -141.0865
  • Logps/chosen: -142.4955
  • Logits/rejected: 0.0425
  • Logits/chosen: -0.0160

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-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 4
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 10
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.7133 0.3 63 0.6946 0.0868 0.0595 0.6000 0.0274 -111.1324 -112.8988 0.5159 0.4902
0.5044 0.6 126 0.6814 0.2402 0.0924 0.6000 0.1478 -110.8034 -111.3656 0.5007 0.4738
0.6555 0.9 189 0.6392 -0.0496 -0.2815 0.7000 0.2319 -114.5420 -114.2632 0.5375 0.5056
0.2983 1.2 252 0.6671 -0.8670 -1.3823 0.5 0.5153 -125.5504 -122.4372 0.4453 0.4053
0.287 1.5 315 0.6743 -1.0040 -1.5229 0.4000 0.5189 -126.9560 -123.8071 0.3434 0.2980
0.313 1.8 378 0.7727 -1.1663 -1.4516 0.4000 0.2853 -126.2434 -125.4304 0.3244 0.2767
0.1026 2.1 441 0.8556 -1.5616 -1.8026 0.4000 0.2410 -129.7528 -129.3835 0.2187 0.1675
0.1738 2.4 504 1.1593 -2.7915 -2.8593 0.4000 0.0677 -140.3199 -141.6827 0.0630 0.0046
0.2095 2.7 567 1.1725 -2.9060 -2.9579 0.4000 0.0519 -141.3057 -142.8270 0.0427 -0.0158
0.0235 3.0 630 1.1519 -2.8728 -2.9359 0.4000 0.0631 -141.0865 -142.4955 0.0425 -0.0160

Framework versions

  • PEFT 0.12.0
  • Transformers 4.45.2
  • Pytorch 2.4.0+cu121
  • Datasets 3.2.0
  • Tokenizers 0.20.3