llama-3.2-3b-sft-2

This model is a fine-tuned version of tanliboy/llama-3.2-3b on the tanliboy/OpenHermes-2.5-reformat dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6744

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-06
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 128
  • total_eval_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 1000
  • training_steps: 10000

Training results

Training Loss Epoch Step Validation Loss
0.7792 0.0673 500 0.7726
0.7496 0.1345 1000 0.7444
0.7243 0.2018 1500 0.7296
0.7178 0.2691 2000 0.7197
0.7077 0.3363 2500 0.7127
0.6992 0.4036 3000 0.7066
0.6992 0.4708 3500 0.7012
0.6945 0.5381 4000 0.6965
0.6879 0.6054 4500 0.6920
0.6901 0.6726 5000 0.6879
0.6759 0.7399 5500 0.6844
0.6752 0.8072 6000 0.6812
0.6826 0.8744 6500 0.6783
0.6804 0.9417 7000 0.6758
0.6131 1.0089 7500 0.6764
0.6012 1.0762 8000 0.6758
0.6136 1.1435 8500 0.6751
0.6127 1.2107 9000 0.6747
0.6076 1.2780 9500 0.6745
0.6033 1.3453 10000 0.6744

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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