Edit model card

llama381binstruct_summarize_short

This model is a fine-tuned version of NousResearch/Meta-Llama-3.1-8B-Instruct on the generator dataset. It achieves the following results on the evaluation set:

  • Loss: 1.9773

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: 0.0002
  • train_batch_size: 1
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 30
  • training_steps: 500

Training results

Training Loss Epoch Step Validation Loss
1.7658 1.3158 25 1.2514
0.798 2.6316 50 1.2960
0.4432 3.9474 75 1.3901
0.1598 5.2632 100 1.6723
0.0867 6.5789 125 1.7080
0.0397 7.8947 150 1.7470
0.0356 9.2105 175 1.7648
0.0225 10.5263 200 1.7194
0.0122 11.8421 225 1.7498
0.0055 13.1579 250 1.8408
0.0034 14.4737 275 1.9249
0.003 15.7895 300 1.8917
0.0027 17.1053 325 1.8668
0.0023 18.4211 350 1.9104
0.0023 19.7368 375 1.9403
0.0022 21.0526 400 1.9561
0.0018 22.3684 425 1.9670
0.0019 23.6842 450 1.9720
0.002 25.0 475 1.9760
0.0015 26.3158 500 1.9773

Framework versions

  • PEFT 0.12.0
  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 3.0.0
  • Tokenizers 0.19.1
Downloads last month
7
Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for Cheselle/llama381binstruct_summarize_short

Adapter
(67)
this model