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G0514HMA26H

This model is a fine-tuned version of google/gemma-2b on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: -17.9022

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: 0.0003
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine_with_restarts
  • lr_scheduler_warmup_steps: 80
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
0.8009 0.09 10 -0.2103
-1.0796 0.18 20 -2.5087
-3.9095 0.27 30 -5.8273
-7.2606 0.36 40 -9.1358
-10.3742 0.45 50 -12.0428
-13.0694 0.54 60 -14.4715
-15.2349 0.63 70 -16.0930
-16.5217 0.73 80 -16.9969
-17.1884 0.82 90 -17.3938
-17.4707 0.91 100 -17.5554
-17.5868 1.0 110 -17.6315
-17.6564 1.09 120 -17.6735
-17.688 1.18 130 -17.7003
-17.709 1.27 140 -17.7200
-17.7262 1.36 150 -17.7362
-17.7401 1.45 160 -17.7476
-17.7557 1.54 170 -17.7664
-17.7777 1.63 180 -17.7896
-17.7948 1.72 190 -17.8078
-17.8232 1.81 200 -17.8337
-17.8393 1.9 210 -17.8518
-17.8561 1.99 220 -17.8679
-17.8673 2.08 230 -17.8730
-17.8748 2.18 240 -17.8887
-17.8874 2.27 250 -17.8931
-17.8901 2.36 260 -17.8972
-17.8918 2.45 270 -17.8974
-17.8952 2.54 280 -17.9002
-17.898 2.63 290 -17.9012
-17.8994 2.72 300 -17.9019
-17.8999 2.81 310 -17.9020
-17.9012 2.9 320 -17.9022
-17.8998 2.99 330 -17.9022

Framework versions

  • Transformers 4.36.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.14.6
  • Tokenizers 0.14.0
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