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metadata
library_name: peft
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
  - llama-factory
  - prefix-tuning
  - generated_from_trainer
model-index:
  - name: train_hellaswag_1754652170
    results: []

train_hellaswag_1754652170

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the hellaswag dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4635
  • Num Input Tokens Seen: 108930064

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-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 123
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10.0

Training results

Training Loss Epoch Step Validation Loss Input Tokens Seen
0.5018 0.5001 4490 0.5131 5450816
0.4862 1.0001 8980 0.4738 10899840
0.4703 1.5002 13470 0.4673 16338976
0.4736 2.0002 17960 0.4660 21789168
0.4783 2.5003 22450 0.4658 27236592
0.4663 3.0003 26940 0.4649 32696128
0.4541 3.5004 31430 0.4646 38137920
0.4581 4.0004 35920 0.4643 43579472
0.4528 4.5005 40410 0.4643 49022960
0.4502 5.0006 44900 0.4639 54468496
0.4639 5.5006 49390 0.4635 59917136
0.4624 6.0007 53880 0.4643 65358976
0.4692 6.5007 58370 0.4642 70806016
0.4549 7.0008 62860 0.4644 76259312
0.4698 7.5008 67350 0.4640 81705616
0.4546 8.0009 71840 0.4641 87153488
0.4462 8.5009 76330 0.4635 92602480
0.4564 9.0010 80820 0.4640 98051504
0.466 9.5011 85310 0.4641 103491728

Framework versions

  • PEFT 0.15.2
  • Transformers 4.51.3
  • Pytorch 2.8.0+cu128
  • Datasets 3.6.0
  • Tokenizers 0.21.1