Experiment-2 / README.md
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metadata
base_model: NousResearch/Llama-2-7b-hf
library_name: peft
metrics:
  - accuracy
  - precision
  - recall
  - f1
tags:
  - generated_from_trainer
model-index:
  - name: Experiment-2
    results: []

Experiment-2

This model is a fine-tuned version of NousResearch/Llama-2-7b-hf on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6750
  • Accuracy: 0.596
  • Precision: 0.5869
  • Recall: 0.6263
  • F1: 0.6060

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: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 64
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
No log 0.9874 54 0.6970 0.532 0.5313 0.4785 0.5035
No log 1.9931 109 0.6923 0.508 0.5103 0.1989 0.2863
0.694 2.9989 164 0.6888 0.5413 0.5303 0.6586 0.5875
0.694 3.9863 218 0.6926 0.5187 0.6279 0.0726 0.1301
0.694 4.992 273 0.6778 0.5947 0.6269 0.4516 0.525
0.6841 5.9977 328 0.6738 0.5827 0.5582 0.7608 0.6439
0.6841 6.9851 382 0.6701 0.5893 0.6301 0.4167 0.5016
0.6841 7.9909 437 0.6717 0.6013 0.5835 0.6855 0.6304
0.6699 8.9966 492 0.6768 0.5787 0.5553 0.7554 0.6401
0.6699 9.8743 540 0.6750 0.596 0.5869 0.6263 0.6060

Framework versions

  • PEFT 0.14.0
  • Transformers 4.46.3
  • Pytorch 2.3.1.post300
  • Datasets 3.2.0
  • Tokenizers 0.20.3