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metadata
library_name: transformers
license: apache-2.0
base_model: tsavage68/Na_M2_1000steps_1e7_SFT
tags:
  - trl
  - dpo
  - generated_from_trainer
model-index:
  - name: Na_M2_1000steps_1e7rate_03beta_cSFTDPO
    results: []

Na_M2_1000steps_1e7rate_03beta_cSFTDPO

This model is a fine-tuned version of tsavage68/Na_M2_1000steps_1e7_SFT on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0000
  • Rewards/chosen: 3.5522
  • Rewards/rejected: -11.1817
  • Rewards/accuracies: 1.0
  • Rewards/margins: 14.7339
  • Logps/rejected: -117.1956
  • Logps/chosen: -36.2917
  • Logits/rejected: -2.4993
  • Logits/chosen: -2.5149

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: 1e-07
  • train_batch_size: 2
  • eval_batch_size: 1
  • 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: 100
  • training_steps: 1000

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.0004 0.2667 50 0.0000 2.3360 -8.0685 1.0 10.4045 -106.8185 -40.3458 -2.5169 -2.5309
0.0 0.5333 100 0.0000 2.8383 -9.2541 1.0 12.0924 -110.7703 -38.6713 -2.5103 -2.5250
0.0 0.8 150 0.0000 3.0920 -9.7555 1.0 12.8475 -112.4418 -37.8257 -2.5067 -2.5217
0.0 1.0667 200 0.0000 3.2037 -10.0769 1.0 13.2806 -113.5130 -37.4533 -2.5051 -2.5202
0.0 1.3333 250 0.0000 3.2784 -10.3241 1.0 13.6025 -114.3372 -37.2044 -2.5046 -2.5198
0.0 1.6 300 0.0000 3.3562 -10.5498 1.0 13.9060 -115.0894 -36.9450 -2.5033 -2.5186
0.0 1.8667 350 0.0000 3.4141 -10.7123 1.0 14.1265 -115.6312 -36.7520 -2.5019 -2.5173
0.0 2.1333 400 0.0000 3.4694 -10.8608 1.0 14.3302 -116.1261 -36.5679 -2.5020 -2.5174
0.0 2.4 450 0.0000 3.4912 -10.9759 1.0 14.4671 -116.5096 -36.4950 -2.5011 -2.5165
0.0 2.6667 500 0.0000 3.5172 -11.0415 1.0 14.5587 -116.7282 -36.4083 -2.5010 -2.5165
0.0 2.9333 550 0.0000 3.5281 -11.1219 1.0 14.6500 -116.9964 -36.3719 -2.4999 -2.5154
0.0 3.2 600 0.0000 3.5544 -11.1376 1.0 14.6920 -117.0486 -36.2843 -2.4985 -2.5140
0.0 3.4667 650 0.0000 3.5412 -11.1686 1.0 14.7098 -117.1519 -36.3284 -2.4993 -2.5149
0.0 3.7333 700 0.0000 3.5592 -11.1405 1.0 14.6997 -117.0585 -36.2685 -2.4988 -2.5143
0.0 4.0 750 0.0000 3.5602 -11.1575 1.0 14.7177 -117.1151 -36.2652 -2.4993 -2.5148
0.0 4.2667 800 0.0000 3.5534 -11.1617 1.0 14.7151 -117.1290 -36.2877 -2.4996 -2.5152
0.0 4.5333 850 0.0000 3.5623 -11.1612 1.0 14.7234 -117.1272 -36.2582 -2.4994 -2.5150
0.0 4.8 900 0.0000 3.5522 -11.1817 1.0 14.7339 -117.1956 -36.2917 -2.4993 -2.5149
0.0 5.0667 950 0.0000 3.5522 -11.1817 1.0 14.7339 -117.1956 -36.2917 -2.4993 -2.5149
0.0 5.3333 1000 0.0000 3.5522 -11.1817 1.0 14.7339 -117.1956 -36.2917 -2.4993 -2.5149

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1