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metadata
tags:
  - generated_from_trainer
model-index:
  - name: TinyLlama-1.1B-Chat-v1.0
    results: []

TinyLlama-1.1B-Chat-v1.0

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5138
  • Rewards/chosen: -0.0274
  • Rewards/rejected: -1.0362
  • Rewards/accuracies: 0.7381
  • Rewards/margins: 1.0087
  • Logps/rejected: -296.0739
  • Logps/chosen: -370.1298
  • Logits/rejected: -2.6565
  • Logits/chosen: -2.7074

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: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • 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: linear
  • lr_scheduler_warmup_ratio: 0.1
  • 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
0.6686 0.1 100 0.6668 0.0624 -0.0106 0.6746 0.0730 -285.8178 -369.2313 -2.7623 -2.8330
0.59 0.21 200 0.5995 0.1603 -0.1926 0.6825 0.3530 -287.6386 -368.2522 -2.7514 -2.8180
0.5843 0.31 300 0.5644 0.2269 -0.3175 0.6905 0.5444 -288.8868 -367.5864 -2.7305 -2.7952
0.5633 0.41 400 0.5476 0.2211 -0.4312 0.7103 0.6523 -290.0246 -367.6447 -2.7100 -2.7725
0.5224 0.52 500 0.5388 0.2702 -0.4543 0.6984 0.7244 -290.2547 -367.1539 -2.6919 -2.7543
0.5689 0.62 600 0.5326 0.3161 -0.4312 0.7302 0.7473 -290.0246 -366.6946 -2.6977 -2.7596
0.5556 0.72 700 0.5296 0.3133 -0.4431 0.7143 0.7565 -290.1436 -366.7222 -2.6960 -2.7563
0.5368 0.83 800 0.5235 0.3087 -0.5008 0.7183 0.8096 -290.7203 -366.7679 -2.6863 -2.7455
0.5324 0.93 900 0.5231 0.3330 -0.4764 0.7381 0.8094 -290.4763 -366.5252 -2.6944 -2.7532
0.4667 1.03 1000 0.5211 0.3442 -0.4815 0.7302 0.8257 -290.5269 -366.4131 -2.6890 -2.7466
0.4516 1.14 1100 0.5197 0.2843 -0.6031 0.7381 0.8874 -291.7431 -367.0122 -2.6770 -2.7325
0.4176 1.24 1200 0.5184 0.2116 -0.7161 0.7460 0.9276 -292.8727 -367.7397 -2.6729 -2.7277
0.446 1.34 1300 0.5187 0.2095 -0.6963 0.7421 0.9058 -292.6750 -367.7603 -2.6740 -2.7278
0.472 1.44 1400 0.5154 0.2233 -0.6454 0.7540 0.8686 -292.1659 -367.6227 -2.6716 -2.7264
0.4425 1.55 1500 0.5158 0.1986 -0.7079 0.7381 0.9065 -292.7915 -367.8694 -2.6695 -2.7244
0.434 1.65 1600 0.5148 0.2037 -0.6841 0.7381 0.8878 -292.5535 -367.8188 -2.6639 -2.7187
0.4209 1.75 1700 0.5146 0.1297 -0.7819 0.7460 0.9116 -293.5308 -368.5582 -2.6636 -2.7185
0.4128 1.86 1800 0.5129 0.1418 -0.7822 0.7381 0.9240 -293.5338 -368.4372 -2.6651 -2.7194
0.4685 1.96 1900 0.5125 0.0967 -0.8256 0.7421 0.9223 -293.9677 -368.8879 -2.6709 -2.7248
0.3605 2.06 2000 0.5130 0.0627 -0.8947 0.7302 0.9574 -294.6591 -369.2281 -2.6689 -2.7211
0.3463 2.17 2100 0.5123 0.0453 -0.9465 0.7421 0.9918 -295.1770 -369.4025 -2.6709 -2.7218
0.362 2.27 2200 0.5125 0.0174 -0.9774 0.7381 0.9948 -295.4861 -369.6811 -2.6628 -2.7140
0.354 2.37 2300 0.5148 0.0053 -0.9919 0.7421 0.9972 -295.6311 -369.8024 -2.6562 -2.7070
0.3539 2.48 2400 0.5144 -0.0049 -0.9987 0.7381 0.9939 -295.6994 -369.9039 -2.6557 -2.7070
0.3374 2.58 2500 0.5143 -0.0015 -1.0170 0.75 1.0156 -295.8826 -369.8703 -2.6616 -2.7128
0.3417 2.68 2600 0.5137 0.0000 -1.0041 0.7341 1.0041 -295.7533 -369.8551 -2.6605 -2.7118
0.3312 2.79 2700 0.5140 -0.0197 -1.0285 0.7302 1.0089 -295.9977 -370.0519 -2.6563 -2.7071
0.3643 2.89 2800 0.5146 -0.0233 -1.0285 0.7421 1.0052 -295.9974 -370.0886 -2.6552 -2.7063
0.3322 2.99 2900 0.5142 -0.0293 -1.0337 0.7302 1.0045 -296.0496 -370.1480 -2.6573 -2.7079

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.2+cu121
  • Datasets 2.14.6
  • Tokenizers 0.14.1