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ft-raft-lora

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

  • Loss: 0.1402

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: 0.0003
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 1399
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 100
  • training_steps: 500

Training results

Training Loss Epoch Step Validation Loss
1.8153 0.8696 20 1.6376
1.3735 1.7391 40 1.1018
0.7809 2.6087 60 0.4950
0.3055 3.4783 80 0.2025
0.1425 4.3478 100 0.1491
0.105 5.2174 120 0.1422
0.0755 6.0870 140 0.1377
0.0602 6.9565 160 0.1402

Framework versions

  • PEFT 0.12.0
  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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