spin-v-high-loss / README.md
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metadata
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
  - generated_from_trainer
model-index:
  - name: spin-v-high-loss
    results: []

spin-v-high-loss

This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0069
  • Rewards/real: -10.1415
  • Rewards/generated: -55.1541
  • Rewards/accuracies: 1.0
  • Rewards/margins: 45.0126
  • Logps/generated: -5640.6729
  • Logps/real: -1151.2217
  • Logits/generated: 3.0744
  • Logits/real: 1.9177

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: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • total_train_batch_size: 32
  • 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: 1

Training results

Training Loss Epoch Step Validation Loss Rewards/real Rewards/generated Rewards/accuracies Rewards/margins Logps/generated Logps/real Logits/generated Logits/real
0.0717 0.13 50 0.0490 -3.1258 -37.3431 0.9907 34.2173 -3859.5708 -449.6532 3.4831 1.9303
0.0323 0.27 100 0.0300 -3.9959 -38.8380 0.9973 34.8421 -4009.0552 -536.6592 -0.0155 -0.1626
0.026 0.4 150 0.0158 -8.2107 -50.0493 0.9947 41.8386 -5130.1880 -958.1443 1.0207 1.0071
0.0106 0.53 200 0.0087 -9.2505 -61.7325 0.9960 52.4820 -6298.5093 -1062.1265 2.2349 1.2992
0.0071 0.67 250 0.0106 -11.4051 -49.3118 0.9987 37.9067 -5056.4409 -1277.5874 2.8798 3.2925
0.0121 0.8 300 0.0074 -9.0224 -49.1152 1.0 40.0928 -5036.7827 -1039.3110 2.8713 2.6792
0.0013 0.93 350 0.0069 -10.1415 -55.1541 1.0 45.0126 -5640.6729 -1151.2217 3.0744 1.9177

Framework versions

  • Transformers 4.37.0
  • Pytorch 2.1.2+cu121
  • Datasets 2.14.6
  • Tokenizers 0.15.2