oo-method-test-model-bylibrary

This model is a fine-tuned version of huggingface/CodeBERTa-small-v1 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1651
• Accuracy: 0.9439
• Best Accuracy: 0.9439

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: 1.238e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.05
• training_steps: 915

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Best Accuracy
0.4914	0.19	183	0.2747	0.8956	0.8956
0.2639	0.37	366	0.3623	0.8925	0.8956
0.2105	0.56	549	0.2257	0.9224	0.9224
0.1669	0.74	732	0.1651	0.9439	0.9439
0.1037	0.93	915	0.1676	0.9408	0.9439

Framework versions

• Transformers 4.33.1
• Pytorch 2.0.1+cu117
• Datasets 2.14.5
• Tokenizers 0.13.3