---
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