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library_name: peft
license: apache-2.0
base_model: Salesforce/codet5-small
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: results_v3
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# results_v3
This model is a fine-tuned version of [Salesforce/codet5-small](https://huggingface.co/Salesforce/codet5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4674
- Accuracy: 0.7824
- Precision: 0.0804
- Recall: 0.6957
- F1 Score: 0.1441
- F2 Score: 0.2749
- Gmean: 0.7388
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score | F2 Score | Gmean |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|:--------:|:------:|
| No log | 1.0 | 70 | 0.6435 | 0.6495 | 0.0450 | 0.6087 | 0.0838 | 0.1737 | 0.6293 |
| 0.769 | 2.0 | 140 | 0.4895 | 0.7995 | 0.0824 | 0.6522 | 0.1463 | 0.2737 | 0.7239 |
| 0.6429 | 3.0 | 210 | 0.4972 | 0.7950 | 0.0806 | 0.6522 | 0.1435 | 0.2698 | 0.7218 |
| 0.6429 | 4.0 | 280 | 0.5368 | 0.7755 | 0.0739 | 0.6522 | 0.1327 | 0.2542 | 0.7127 |
| 0.6276 | 5.0 | 350 | 0.4395 | 0.8064 | 0.0805 | 0.6087 | 0.1421 | 0.2632 | 0.7029 |
| 0.5782 | 6.0 | 420 | 0.4263 | 0.8167 | 0.0898 | 0.6522 | 0.1579 | 0.2896 | 0.7318 |
| 0.5782 | 7.0 | 490 | 0.4501 | 0.7973 | 0.0815 | 0.6522 | 0.1449 | 0.2717 | 0.7228 |
| 0.5599 | 8.0 | 560 | 0.4610 | 0.7950 | 0.0806 | 0.6522 | 0.1435 | 0.2698 | 0.7218 |
| 0.5624 | 9.0 | 630 | 0.5381 | 0.7595 | 0.0807 | 0.7826 | 0.1463 | 0.2857 | 0.7706 |
| 0.5356 | 10.0 | 700 | 0.4899 | 0.7755 | 0.0780 | 0.6957 | 0.1404 | 0.2694 | 0.7355 |
| 0.5356 | 11.0 | 770 | 0.5032 | 0.7675 | 0.0794 | 0.7391 | 0.1435 | 0.2778 | 0.7535 |
| 0.5576 | 12.0 | 840 | 0.4943 | 0.7709 | 0.0806 | 0.7391 | 0.1453 | 0.2805 | 0.7553 |
| 0.5145 | 13.0 | 910 | 0.4752 | 0.7801 | 0.0837 | 0.7391 | 0.1504 | 0.2881 | 0.7599 |
| 0.5145 | 14.0 | 980 | 0.4725 | 0.7824 | 0.0846 | 0.7391 | 0.1518 | 0.2901 | 0.7610 |
| 0.531 | 15.0 | 1050 | 0.4674 | 0.7824 | 0.0804 | 0.6957 | 0.1441 | 0.2749 | 0.7388 |
### Framework versions
- PEFT 0.14.0
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0 |