mamiksik's picture
update model card README.md
5637eb3
|
raw
history blame
2.74 kB
metadata
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: CodeBERTa-commit-message-autocomplete
    results: []

CodeBERTa-commit-message-autocomplete

This model is a fine-tuned version of microsoft/codebert-base-mlm on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7327
  • Accuracy: 0.6612

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: 2e-05
  • train_batch_size: 42
  • eval_batch_size: 42
  • seed: 42
  • gradient_accumulation_steps: 3
  • total_train_batch_size: 126
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 50
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 325 2.6847 0.5185
3.367 2.0 650 2.4055 0.5573
3.367 3.0 975 2.2742 0.5766
2.4354 4.0 1300 2.1065 0.6057
2.1925 5.0 1625 2.0764 0.6053
2.1925 6.0 1950 2.0169 0.6172
2.0217 7.0 2275 1.9270 0.6209
1.9424 8.0 2600 1.9326 0.6318
1.9424 9.0 2925 1.8849 0.6321
1.8485 10.0 3250 1.8834 0.6422
1.7847 11.0 3575 1.8213 0.6481
1.7847 12.0 3900 1.8674 0.6374
1.719 13.0 4225 1.7865 0.6473
1.6847 14.0 4550 1.8005 0.6523
1.6847 15.0 4875 1.8039 0.6516
1.6274 16.0 5200 1.7457 0.6617
1.5833 17.0 5525 1.7456 0.6526
1.5833 18.0 5850 1.7314 0.6626
1.5485 19.0 6175 1.7605 0.6590
1.5448 20.0 6500 1.7694 0.6592
1.5448 21.0 6825 1.7327 0.6612

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1
  • Tokenizers 0.13.2