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pmrster/test-llama3-8b-instruct-qlora-fine-tune-1
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metadata
license: llama3
library_name: peft
tags:
  - generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B-Instruct
model-index:
  - name: llama3-8b-instruct-journal-finetune
    results: []

llama3-8b-instruct-journal-finetune

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 2.0299

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: 2.5e-05
  • train_batch_size: 2
  • 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: 1
  • training_steps: 500

Training results

Training Loss Epoch Step Validation Loss
2.9002 2.0833 25 1.8777
1.1645 4.1667 50 1.6214
0.4078 6.25 75 1.7856
0.2373 8.3333 100 1.8434
0.2209 10.4167 125 1.7767
0.1953 12.5 150 1.8293
0.1755 14.5833 175 1.7663
0.1893 16.6667 200 1.8726
0.1621 18.75 225 1.9366
0.1657 20.8333 250 1.9146
0.1593 22.9167 275 1.9225
0.156 25.0 300 1.9411
0.1549 27.0833 325 1.9504
0.1525 29.1667 350 1.9608
0.1511 31.25 375 1.9924
0.1494 33.3333 400 1.9878
0.1488 35.4167 425 2.0089
0.1479 37.5 450 2.0089
0.1448 39.5833 475 2.0233
0.1447 41.6667 500 2.0299

Framework versions

  • PEFT 0.11.1
  • Transformers 4.41.1
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1