Federic / lora-fine-tuning-llama2-SQL-lora-codellama

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Introduction of lora-fine-tuning-llama2-SQL-lora-codellama

Model Details of lora-fine-tuning-llama2-SQL-lora-codellama

lora-fine-tuning-llama2-SQL-lora-codellama

This model is a fine-tuned version of codellama/CodeLlama-7b-hf on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5720
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: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 3
  • total_train_batch_size: 12
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.03
  • num_epochs: 1
Training results
Training Loss Epoch Step Validation Loss
2.7803 0.06 5 2.5059
1.2647 0.12 10 1.1731
0.8026 0.18 15 0.8834
0.6482 0.24 20 0.8281
0.8146 0.3 25 0.7858
0.7458 0.36 30 0.7275
0.5377 0.42 35 0.6520
0.5659 0.48 40 0.6560
0.6104 0.54 45 0.6101
0.6253 0.6 50 0.6024
0.4878 0.66 55 0.5891
0.4777 0.72 60 0.5830
0.634 0.78 65 0.5831
0.5562 0.84 70 0.5771
0.4696 0.9 75 0.5734
0.4193 0.96 80 0.5720
Framework versions
  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1

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