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CodeLlama-13b-Instruct-hf_En__size_52_epochs_10_2024-06-21_06-37-42_3556410

This model is a fine-tuned version of codellama/CodeLlama-13b-Instruct-hf on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.6986
  • Accuracy: 0.052
  • Chrf: 0.682
  • Bleu: 0.599
  • Sacrebleu: 0.6
  • Rouge1: 0.651
  • Rouge2: 0.434
  • Rougel: 0.601
  • Rougelsum: 0.644
  • Meteor: 0.54

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: 0.001
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 3407
  • distributed_type: multi-GPU
  • num_devices: 4
  • total_train_batch_size: 4
  • total_eval_batch_size: 4
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 52
  • training_steps: 520

Training results

Training Loss Epoch Step Validation Loss Accuracy Chrf Bleu Sacrebleu Rouge1 Rouge2 Rougel Rougelsum Meteor
0.5377 4.0 52 1.6208 0.06 0.637 0.525 0.5 0.619 0.387 0.564 0.608 0.488
0.932 8.0 104 2.1202 0.05 0.554 0.452 0.5 0.569 0.313 0.515 0.566 0.485
0.3679 12.0 156 1.9634 0.049 0.606 0.488 0.5 0.594 0.371 0.549 0.59 0.491
0.3454 16.0 208 1.9613 0.053 0.601 0.487 0.5 0.571 0.325 0.524 0.566 0.504
0.3294 20.0 260 1.8641 0.05 0.638 0.536 0.5 0.611 0.388 0.568 0.604 0.516
0.5272 24.0 312 1.8354 0.052 0.644 0.535 0.5 0.609 0.368 0.559 0.603 0.531
0.1871 28.0 364 1.7705 0.054 0.659 0.568 0.6 0.627 0.41 0.586 0.624 0.54
0.4867 32.0 416 1.7689 0.052 0.665 0.571 0.6 0.63 0.406 0.579 0.624 0.562
0.1634 36.0 468 1.6964 0.052 0.682 0.601 0.6 0.658 0.444 0.605 0.65 0.538
0.3475 40.0 520 1.6986 0.052 0.682 0.599 0.6 0.651 0.434 0.601 0.644 0.54

Framework versions

  • Transformers 4.37.0
  • Pytorch 2.2.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.15.2
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