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metadata
license: apache-2.0
library_name: peft
tags:
  - trl
  - sft
  - unsloth
  - generated_from_trainer
base_model: unsloth/llama-3-8b-Instruct-bnb-4bit
model-index:
  - name: llama3-chat_50000_500
    results: []

llama3-chat_50000_500

This model is a fine-tuned version of unsloth/llama-3-8b-Instruct-bnb-4bit on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7378

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: 16
  • eval_batch_size: 16
  • seed: 3407
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 5
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss
1.7748 0.128 100 1.4928
1.5097 0.256 200 1.4743
1.5122 0.384 300 1.4623
1.4924 0.512 400 1.4609
1.485 0.64 500 1.4526
1.4779 0.768 600 1.4511
1.4728 0.896 700 1.4446
1.4476 1.024 800 1.4512
1.3725 1.152 900 1.4558
1.3747 1.28 1000 1.4560
1.3735 1.408 1100 1.4548
1.3717 1.536 1200 1.4499
1.3694 1.6640 1300 1.4526
1.3698 1.792 1400 1.4542
1.3701 1.92 1500 1.4512
1.3004 2.048 1600 1.4977
1.1904 2.176 1700 1.5075
1.1977 2.304 1800 1.5041
1.1888 2.432 1900 1.5094
1.1885 2.56 2000 1.5024
1.1989 2.6880 2100 1.5039
1.1905 2.816 2200 1.5046
1.1914 2.944 2300 1.5077
1.0764 3.072 2400 1.6027
0.9757 3.2 2500 1.6227
0.9768 3.328 2600 1.6228
0.9795 3.456 2700 1.6225
0.9775 3.584 2800 1.6190
0.9781 3.7120 2900 1.6164
0.981 3.84 3000 1.6199
0.9812 3.968 3100 1.6254
0.8731 4.096 3200 1.7307
0.8376 4.224 3300 1.7343
0.8352 4.352 3400 1.7398
0.8429 4.48 3500 1.7357
0.8431 4.608 3600 1.7386
0.8383 4.736 3700 1.7380
0.8375 4.864 3800 1.7376
0.842 4.992 3900 1.7378

Framework versions

  • PEFT 0.10.0
  • Transformers 4.40.2
  • Pytorch 2.3.0
  • Datasets 2.19.1
  • Tokenizers 0.19.1