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rm_llama3_8B_helpsteer2

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1203
  • Accuracy: 0.6339

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: 32
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 10
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.8471 0.1572 50 0.7326 0.5819
0.7455 0.3145 100 0.6821 0.5549
0.7059 0.4717 150 0.6642 0.6050
0.6926 0.6289 200 0.6707 0.5915
0.6683 0.7862 250 0.6506 0.6320
0.6727 0.9434 300 0.6456 0.6224
0.629 1.1006 350 0.6218 0.6551
0.5446 1.2579 400 0.6604 0.6281
0.5377 1.4151 450 0.6345 0.6455
0.5555 1.5723 500 0.6145 0.6320
0.5645 1.7296 550 0.6178 0.6474
0.5392 1.8868 600 0.6323 0.6532
0.4505 2.0440 650 0.7539 0.6455
0.1406 2.2013 700 1.0884 0.6339
0.1487 2.3585 750 1.1136 0.6339
0.1493 2.5157 800 1.1202 0.6358
0.1259 2.6730 850 1.1253 0.6320
0.1382 2.8302 900 1.1189 0.6320
0.1448 2.9874 950 1.1203 0.6339

Framework versions

  • Transformers 4.43.4
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.2
  • Tokenizers 0.19.1
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