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medllama3-v20-with-prefix_prompt

PEFT
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medllama3-v20-with-prefix_prompt / README.md
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metadata
library_name: peft
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: medllama3-v20-with-prefix_prompt
    results: []

medllama3-v20-with-prefix_prompt

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: 0.8028
  • Balanced Accuracy: 0.5960
  • Accuracy: 0.5457

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: 1e-05
  • train_batch_size: 4
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • 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: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Balanced Accuracy Accuracy
1.7999 1.0 165 0.6813 0.6104 0.6187
1.7523 2.0 330 0.6623 0.5918 0.4087
2.1806 3.0 495 0.6799 0.6413 0.4269
1.3861 4.0 660 0.7232 0.6363 0.4452
1.6961 5.0 825 0.8122 0.6428 0.3721
1.4074 6.0 990 0.8685 0.6400 0.6735
1.3749 7.0 1155 0.6330 0.6409 0.6598
1.3455 8.0 1320 0.6396 0.6594 0.4886
1.3391 9.0 1485 0.6102 0.6464 0.5845
1.4026 10.0 1650 0.6464 0.6058 0.6142
1.2097 11.0 1815 0.7539 0.6151 0.6644
1.178 12.0 1980 0.6004 0.6539 0.6210
1.1876 13.0 2145 0.6344 0.6308 0.6279
1.1125 14.0 2310 0.6716 0.6598 0.6507
1.0532 15.0 2475 0.7006 0.6501 0.5548
1.0158 16.0 2640 0.6975 0.6445 0.6050
0.9504 17.0 2805 0.8028 0.5960 0.5457

Framework versions

  • PEFT 0.14.0
  • Transformers 4.48.1
  • Pytorch 2.1.0
  • Datasets 3.2.0
  • Tokenizers 0.21.0