v-alpha-tross / README.md
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metadata
tags:
  - generated_from_trainer
model-index:
  - name: completed-model
    results: []

Built with Axolotl

completed-model

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

  • Loss: 0.3186
  • Rewards/chosen: -0.6296
  • Rewards/rejected: -2.5591
  • Rewards/accuracies: 0.8571
  • Rewards/margins: 1.9295
  • Logps/rejected: -296.3221
  • Logps/chosen: -425.5087
  • Logits/rejected: -2.2481
  • Logits/chosen: -1.7413

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: 3
  • eval_batch_size: 3
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 40
  • total_train_batch_size: 120
  • total_eval_batch_size: 120
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 18
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.4772 0.1 61 0.4037 -0.3256 -1.2099 0.8095 0.8843 -282.8301 -422.4691 -2.1649 -1.6678
0.3859 0.2 122 0.3681 -0.3816 -1.7445 0.7143 1.3629 -288.1762 -423.0287 -2.2536 -1.7385
0.3061 0.3 183 0.3546 -0.4969 -2.1025 0.8095 1.6056 -291.7559 -424.1818 -2.1989 -1.7108
0.3765 0.4 244 0.3374 -0.5153 -2.1301 0.7619 1.6148 -292.0326 -424.3660 -2.2182 -1.7222
0.2819 0.5 305 0.3303 -0.4402 -2.1809 0.8095 1.7407 -292.5404 -423.6147 -2.1835 -1.6998
0.3009 0.6 366 0.3314 -0.8026 -2.7756 0.8571 1.9730 -298.4871 -427.2388 -2.2430 -1.7529
0.3015 0.7 427 0.3228 -0.6439 -2.5710 0.9048 1.9271 -296.4410 -425.6519 -2.2258 -1.7303
0.3407 0.8 488 0.3185 -0.7270 -2.7118 0.8571 1.9847 -297.8488 -426.4829 -2.2530 -1.7496
0.3149 0.9 549 0.3186 -0.6296 -2.5591 0.8571 1.9295 -296.3221 -425.5087 -2.2481 -1.7413

Framework versions

  • Transformers 4.35.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.7
  • Tokenizers 0.14.1