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deepseek-coder-6.7b-instruct_Fi__translations_size_104_epochs_10_2024-06-21_23-44-44_3557640

This model is a fine-tuned version of deepseek-ai/deepseek-coder-6.7b-instruct on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 2.9391
  • Accuracy: 0.027
  • Chrf: 0.526
  • Bleu: 0.433
  • Sacrebleu: 0.4
  • Rouge1: 0.512
  • Rouge2: 0.258
  • Rougel: 0.471
  • Rougelsum: 0.507
  • Meteor: 0.438

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: 104
  • training_steps: 1040

Training results

Training Loss Epoch Step Validation Loss Accuracy Chrf Bleu Sacrebleu Rouge1 Rouge2 Rougel Rougelsum Meteor
0.1525 4.0 104 1.1253 0.014 0.725 0.595 0.6 0.702 0.477 0.625 0.693 0.513
0.1027 8.0 208 1.2219 0.014 0.711 0.58 0.6 0.684 0.45 0.611 0.673 0.51
0.1307 12.0 312 1.3506 0.025 0.709 0.606 0.6 0.689 0.472 0.616 0.679 0.545
1.0101 16.0 416 1.6526 0.017 0.706 0.614 0.6 0.696 0.494 0.629 0.687 0.532
0.177 20.0 520 2.0077 0.028 0.663 0.558 0.6 0.659 0.439 0.594 0.653 0.46
0.2181 24.0 624 2.4044 0.02 0.615 0.507 0.5 0.623 0.393 0.565 0.617 0.474
0.9954 28.0 728 2.5812 0.025 0.585 0.483 0.5 0.579 0.329 0.523 0.569 0.452
0.28 32.0 832 2.8603 0.034 0.548 0.462 0.5 0.543 0.299 0.499 0.538 0.424
0.3616 36.0 936 2.9194 0.031 0.532 0.436 0.4 0.522 0.266 0.476 0.516 0.437
0.3022 40.0 1040 2.9391 0.027 0.526 0.433 0.4 0.512 0.258 0.471 0.507 0.438

Framework versions

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