metadata
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: code-search-net-tokenizer
results: []
code-search-net-tokenizer
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0619
- Precision: 0.9355
- Recall: 0.9502
- F1: 0.9428
- Accuracy: 0.9860
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0749 | 1.0 | 1756 | 0.0704 | 0.8997 | 0.9303 | 0.9148 | 0.9805 |
| 0.0367 | 2.0 | 3512 | 0.0636 | 0.9378 | 0.9497 | 0.9437 | 0.9858 |
| 0.0243 | 3.0 | 5268 | 0.0619 | 0.9355 | 0.9502 | 0.9428 | 0.9860 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2