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End of training
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metadata
license: apache-2.0
base_model: nnheui/pythia-1.4b-sft-full
tags:
  - alignment-handbook
  - trl
  - dpo
  - generated_from_trainer
  - trl
  - dpo
  - alignment-handbook
  - generated_from_trainer
datasets:
  - HuggingFaceH4/ultrafeedback_binarized
model-index:
  - name: pythia-1.4b-dpo-full
    results: []

pythia-1.4b-dpo-full

This model is a fine-tuned version of nnheui/pythia-1.4b-sft-full on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5991
  • Rewards/chosen: -1.875
  • Rewards/rejected: -2.6406
  • Rewards/accuracies: 0.7164
  • Rewards/margins: 0.7734
  • Logps/rejected: -604.0
  • Logps/chosen: -580.0
  • Logits/rejected: -1.4297
  • Logits/chosen: -1.4062
  • Logps/chosen Top Tokens: -0.0009
  • Logps/rejected Top Tokens: -0.0009
  • Logps/chosen Bottom Tokens: -13.9375
  • Logps/rejected Bottom Tokens: -13.8125

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: 5
  • eval_batch_size: 5
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 6
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 120
  • total_eval_batch_size: 30
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10

Training results

Training Loss Epoch Step Logits/chosen Logits/rejected Logps/chosen Logps/chosen Bottom Tokens Logps/chosen Top Tokens Logps/rejected Logps/rejected Bottom Tokens Logps/rejected Top Tokens Validation Loss Rewards/accuracies Rewards/chosen Rewards/margins Rewards/rejected
0.678 0.1963 100 -1.0938 -1.1562 -396.0 -14.0625 -0.0009 -344.0 -14.0 -0.0009 0.6789 0.5881 -0.0275 0.0332 -0.0608
0.645 0.3925 200 -1.1562 -1.2031 -422.0 -14.375 -0.0009 -380.0 -14.3125 -0.0009 0.6489 0.6448 -0.2871 0.1367 -0.4238
0.6396 0.5888 300 -1.1875 -1.2344 -438.0 -14.375 -0.0007 -406.0 -14.3125 -0.0008 0.6304 0.6627 -0.4512 0.2275 -0.6797
0.6102 0.7851 400 -1.1875 -1.2344 -444.0 -14.3125 -0.0007 -414.0 -14.25 -0.0007 0.6268 0.6567 -0.5039 0.2578 -0.7617
0.6084 0.9814 500 -1.1953 -1.2422 -446.0 -14.375 -0.0007 -416.0 -14.3125 -0.0007 0.6259 0.6567 -0.5234 0.2617 -0.7852
0.6115 1.1776 600 0.6121 -0.5547 -0.8789 0.6806 0.3242 -426.0 -450.0 -1.2578 -1.2109 -0.0006 -0.0006 -14.25 -14.125
0.607 1.3739 700 0.6068 -0.6641 -1.0078 0.6985 0.3418 -438.0 -460.0 -1.2812 -1.2344 -0.0006 -0.0006 -14.1875 -14.125
0.5764 1.5702 800 0.5996 -0.75 -1.1406 0.6866 0.3887 -452.0 -468.0 -1.3125 -1.2656 -0.0007 -0.0007 -14.25 -14.125
0.5903 1.7664 900 0.5984 -0.5898 -0.9648 0.7045 0.3770 -434.0 -452.0 -1.3125 -1.2656 -0.0006 -0.0006 -14.25 -14.125
0.5697 1.9627 1000 0.5922 -0.7383 -1.1562 0.6866 0.4160 -454.0 -468.0 -1.3125 -1.2734 -0.0007 -0.0006 -14.0625 -14.0
0.5573 2.1590 1100 0.5854 -0.8203 -1.2812 0.6985 0.4570 -466.0 -476.0 -1.3281 -1.2891 -0.0006 -0.0006 -14.125 -14.0
0.5439 2.3553 1200 0.5845 -1.1016 -1.6172 0.6866 0.5078 -498.0 -504.0 -1.3672 -1.3281 -0.0007 -0.0006 -14.0625 -13.9375
0.5487 2.5515 1300 0.5801 -0.8906 -1.3828 0.6925 0.4980 -476.0 -482.0 -1.3828 -1.3438 -0.0007 -0.0006 -14.0625 -14.0
0.543 2.7478 1400 0.5785 -0.8672 -1.3516 0.7134 0.4863 -474.0 -480.0 -1.375 -1.3359 -0.0007 -0.0006 -14.0625 -13.9375
0.5382 2.9441 1500 0.5711 -1.1172 -1.6641 0.6955 0.5508 -504.0 -506.0 -1.3906 -1.3516 -0.0007 -0.0006 -14.125 -14.0
0.5117 3.1403 1600 0.5712 -1.25 -1.8281 0.7045 0.5742 -520.0 -520.0 -1.3984 -1.3594 -0.0007 -0.0006 -14.125 -14.0
0.4983 3.3366 1700 0.5703 -1.1641 -1.75 0.7015 0.5859 -512.0 -510.0 -1.4062 -1.3672 -0.0007 -0.0007 -14.125 -14.0
0.4976 3.5329 1800 0.5709 -1.2656 -1.8828 0.7254 0.6133 -524.0 -520.0 -1.4141 -1.375 -0.0007 -0.0007 -14.125 -14.0625
0.4956 3.7291 1900 0.5754 -1.2266 -1.8047 0.7164 0.5781 -516.0 -516.0 -1.4062 -1.3672 -0.0008 -0.0008 -14.0625 -13.9375
0.4996 3.9254 2000 0.5722 -1.2578 -1.8516 0.7045 0.6016 -524.0 -520.0 -1.4062 -1.375 -0.0008 -0.0008 -14.0625 -13.9375
0.4588 4.1217 2100 0.5748 -1.4141 -2.0312 0.7343 0.6211 -540.0 -536.0 -1.4062 -1.375 -0.0009 -0.0009 -14.0 -13.875
0.4555 4.3180 2200 0.5743 -1.2969 -1.9141 0.7164 0.6172 -528.0 -524.0 -1.4219 -1.3906 -0.0009 -0.0009 -13.9375 -13.8125
0.4625 4.5142 2300 0.5735 -1.3047 -1.9297 0.7134 0.625 -532.0 -524.0 -1.4141 -1.3828 -0.0008 -0.0008 -14.0 -13.875
0.469 4.7105 2400 0.5743 -1.4766 -2.1406 0.7194 0.6562 -552.0 -540.0 -1.4375 -1.3984 -0.0009 -0.0009 -14.0 -13.875
0.4796 4.9068 2500 0.5750 -1.3281 -1.9766 0.7134 0.6484 -536.0 -528.0 -1.4375 -1.3984 -0.0009 -0.0009 -14.0 -13.875
0.4082 5.1030 2600 0.5818 -1.6016 -2.2656 0.7194 0.6602 -564.0 -552.0 -1.4453 -1.4062 -0.0009 -0.0009 -14.0 -13.875
0.4193 5.2993 2700 0.5803 -1.4922 -2.1406 0.7194 0.6523 -552.0 -544.0 -1.4375 -1.3984 -0.0009 -0.0009 -14.0 -13.8125
0.419 5.4956 2800 0.5795 -1.625 -2.3281 0.7194 0.7031 -572.0 -556.0 -1.4375 -1.3984 -0.0009 -0.0009 -14.0 -13.875
0.4267 5.6919 2900 0.5780 -1.6875 -2.375 0.7134 0.6836 -576.0 -564.0 -1.4375 -1.4062 -0.0009 -0.0008 -13.9375 -13.8125
0.402 5.8881 3000 0.5828 -1.6484 -2.3594 0.7254 0.7109 -572.0 -560.0 -1.4453 -1.4062 -0.0009 -0.0009 -13.9375 -13.8125
0.3656 6.0844 3100 0.5844 -1.6875 -2.4062 0.7015 0.7227 -580.0 -564.0 -1.4375 -1.4062 -0.0009 -0.0009 -14.0 -13.875
0.3971 6.2807 3200 0.5873 -1.6094 -2.3281 0.7075 0.7148 -572.0 -556.0 -1.4453 -1.4141 -0.0009 -0.0009 -14.0 -13.8125
0.3923 6.4769 3300 0.5906 -1.6875 -2.4062 0.7075 0.7188 -580.0 -564.0 -1.4453 -1.4141 -0.0009 -0.0009 -14.0 -13.875
0.4011 6.6732 3400 0.5848 -1.7109 -2.4375 0.7254 0.7344 -584.0 -564.0 -1.4375 -1.4062 -0.0009 -0.0008 -14.0 -13.875
0.3838 6.8695 3500 0.5897 -1.75 -2.4844 0.7164 0.7305 -584.0 -568.0 -1.4297 -1.3984 -0.0009 -0.0008 -13.9375 -13.8125
0.3762 7.0658 3600 0.5910 -1.7812 -2.5312 0.7134 0.7422 -592.0 -572.0 -1.4375 -1.4062 -0.0009 -0.0008 -13.9375 -13.8125
0.3591 7.2620 3700 0.5895 -1.7812 -2.5312 0.7075 0.7578 -592.0 -572.0 -1.4375 -1.4062 -0.0009 -0.0009 -14.0 -13.875
0.3713 7.4583 3800 0.5956 -1.7734 -2.5312 0.7164 0.75 -592.0 -572.0 -1.4297 -1.3984 -0.0009 -0.0009 -13.9375 -13.8125
0.381 7.6546 3900 0.5948 -1.8672 -2.625 0.7164 0.7695 -600.0 -580.0 -1.4375 -1.4062 -0.0009 -0.0008 -13.9375 -13.8125
0.3639 7.8508 4000 0.5950 -1.8672 -2.625 0.7194 0.7578 -600.0 -580.0 -1.4375 -1.4062 -0.0009 -0.0009 -13.9375 -13.8125
0.3563 8.0471 4100 0.5939 -1.8281 -2.5781 0.7075 0.7539 -596.0 -576.0 -1.4297 -1.3984 -0.0009 -0.0009 -13.9375 -13.8125
0.3484 8.2434 4200 0.5969 -1.875 -2.6406 0.7045 0.7656 -600.0 -580.0 -1.4375 -1.4062 -0.0009 -0.0008 -14.0 -13.875
0.3359 8.4396 4300 0.5966 -1.8828 -2.6562 0.7045 0.7734 -604.0 -580.0 -1.4375 -1.4062 -0.0009 -0.0009 -13.9375 -13.8125
0.3639 8.6359 4400 0.5979 -1.8516 -2.5938 0.7075 0.7461 -596.0 -580.0 -1.4297 -1.3984 -0.0009 -0.0009 -13.9375 -13.8125
0.3563 8.8322 4500 0.5979 -1.8594 -2.625 0.7075 0.7617 -600.0 -580.0 -1.4297 -1.3984 -0.0009 -0.0009 -13.9375 -13.8125
0.353 9.0285 4600 0.5981 -1.8672 -2.625 0.6985 0.7617 -600.0 -580.0 -1.4297 -1.3984 -0.0009 -0.0008 -13.9375 -13.8125
0.3514 9.2247 4700 0.5979 -1.8594 -2.625 0.6985 0.7656 -600.0 -580.0 -1.4297 -1.3984 -0.0009 -0.0008 -13.9375 -13.8125
0.3434 9.4210 4800 0.5973 -1.8672 -2.6406 0.7015 0.7656 -600.0 -580.0 -1.4297 -1.4062 -0.0009 -0.0008 -13.9375 -13.8125
0.3492 9.6173 4900 0.5981 -1.875 -2.6406 0.7045 0.7578 -600.0 -580.0 -1.4297 -1.3984 -0.0009 -0.0008 -13.9375 -13.8125
0.3487 9.8135 5000 0.5967 -1.8672 -2.6406 0.7134 0.7734 -600.0 -580.0 -1.4375 -1.4062 -0.0009 -0.0008 -13.9375 -13.8125

Framework versions

  • Transformers 4.40.0
  • Pytorch 2.2.2+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1