sft_10000

This model is a fine-tuned version of mistralai/Mistral-Nemo-Instruct-2407 on the heat_transfer_10000 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0007

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: 0.0001
  • train_batch_size: 12
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 2
  • total_train_batch_size: 24
  • total_eval_batch_size: 2
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss
0.0083 0.0533 20 0.0029
0.0028 0.1067 40 0.0026
0.0028 0.16 60 0.0022
0.0016 0.2133 80 0.0013
0.0012 0.2667 100 0.0011
0.001 0.32 120 0.0008
0.0013 0.3733 140 0.0009
0.0009 0.4267 160 0.0010
0.0008 0.48 180 0.0010
0.0008 0.5333 200 0.0008
0.0005 0.5867 220 0.0007
0.0009 0.64 240 0.0008
0.0008 0.6933 260 0.0010
0.0007 0.7467 280 0.0007
0.0008 0.8 300 0.0008
0.0007 0.8533 320 0.0007
0.0007 0.9067 340 0.0007
0.0007 0.96 360 0.0007

Framework versions

  • PEFT 0.12.0
  • Transformers 4.46.0
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.20.1
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