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G0514HMA15H

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: -17.8971

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: 100
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
0.9162 0.09 10 0.0830
-0.7664 0.18 20 -2.0466
-3.27 0.27 30 -4.9484
-6.242 0.36 40 -7.9963
-9.1799 0.45 50 -10.7742
-11.7646 0.54 60 -13.2319
-14.1063 0.63 70 -15.1473
-15.7143 0.73 80 -16.3945
-16.7127 0.82 90 -17.0741
-17.2299 0.91 100 -17.4041
-17.4683 1.0 110 -17.5479
-17.5857 1.09 120 -17.6235
-17.6418 1.18 130 -17.6631
-17.6771 1.27 140 -17.6957
-17.703 1.36 150 -17.7160
-17.7218 1.45 160 -17.7272
-17.7369 1.54 170 -17.7463
-17.7561 1.63 180 -17.7646
-17.7704 1.72 190 -17.7808
-17.7897 1.81 200 -17.7972
-17.8056 1.9 210 -17.8223
-17.8326 1.99 220 -17.8447
-17.8508 2.08 230 -17.8658
-17.8699 2.18 240 -17.8773
-17.8777 2.27 250 -17.8862
-17.8827 2.36 260 -17.8912
-17.889 2.45 270 -17.8936
-17.8917 2.54 280 -17.8948
-17.8936 2.63 290 -17.8942
-17.8949 2.72 300 -17.8967
-17.8934 2.81 310 -17.8970
-17.8964 2.9 320 -17.8971
-17.8956 2.99 330 -17.8971

Framework versions

  • Transformers 4.36.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.14.6
  • Tokenizers 0.14.0
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Model size
2.52B params
Tensor type
F32
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