End of training
Browse files
README.md
ADDED
|
@@ -0,0 +1,71 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: bsd-3-clause
|
| 3 |
+
base_model: Salesforce/codet5p-220m
|
| 4 |
+
tags:
|
| 5 |
+
- generated_from_trainer
|
| 6 |
+
metrics:
|
| 7 |
+
- accuracy
|
| 8 |
+
- precision
|
| 9 |
+
- recall
|
| 10 |
+
model-index:
|
| 11 |
+
- name: Salesforce-codet5p-220m-finetuned-defect-cwe-group
|
| 12 |
+
results: []
|
| 13 |
+
---
|
| 14 |
+
|
| 15 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 16 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 17 |
+
|
| 18 |
+
# Salesforce-codet5p-220m-finetuned-defect-cwe-group
|
| 19 |
+
|
| 20 |
+
This model is a fine-tuned version of [Salesforce/codet5p-220m](https://huggingface.co/Salesforce/codet5p-220m) on an unknown dataset.
|
| 21 |
+
It achieves the following results on the evaluation set:
|
| 22 |
+
- Loss: 0.5618
|
| 23 |
+
- Accuracy: 0.7428
|
| 24 |
+
- Precision: 0.5937
|
| 25 |
+
- Recall: 0.4798
|
| 26 |
+
|
| 27 |
+
## Model description
|
| 28 |
+
|
| 29 |
+
More information needed
|
| 30 |
+
|
| 31 |
+
## Intended uses & limitations
|
| 32 |
+
|
| 33 |
+
More information needed
|
| 34 |
+
|
| 35 |
+
## Training and evaluation data
|
| 36 |
+
|
| 37 |
+
More information needed
|
| 38 |
+
|
| 39 |
+
## Training procedure
|
| 40 |
+
|
| 41 |
+
### Training hyperparameters
|
| 42 |
+
|
| 43 |
+
The following hyperparameters were used during training:
|
| 44 |
+
- learning_rate: 2e-05
|
| 45 |
+
- train_batch_size: 8
|
| 46 |
+
- eval_batch_size: 8
|
| 47 |
+
- seed: 4711
|
| 48 |
+
- gradient_accumulation_steps: 4
|
| 49 |
+
- total_train_batch_size: 32
|
| 50 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 51 |
+
- lr_scheduler_type: linear
|
| 52 |
+
- num_epochs: 5
|
| 53 |
+
- mixed_precision_training: Native AMP
|
| 54 |
+
|
| 55 |
+
### Training results
|
| 56 |
+
|
| 57 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall |
|
| 58 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|
|
| 59 |
+
| No log | 1.0 | 462 | 0.6991 | 0.6911 | 0.6402 | 0.3911 |
|
| 60 |
+
| 0.803 | 2.0 | 925 | 0.6093 | 0.7192 | 0.6387 | 0.4320 |
|
| 61 |
+
| 0.6422 | 3.0 | 1387 | 0.5770 | 0.7254 | 0.5693 | 0.4681 |
|
| 62 |
+
| 0.5365 | 4.0 | 1850 | 0.5672 | 0.7248 | 0.5682 | 0.4721 |
|
| 63 |
+
| 0.4489 | 4.99 | 2310 | 0.5618 | 0.7428 | 0.5937 | 0.4798 |
|
| 64 |
+
|
| 65 |
+
|
| 66 |
+
### Framework versions
|
| 67 |
+
|
| 68 |
+
- Transformers 4.38.1
|
| 69 |
+
- Pytorch 2.2.1+cu121
|
| 70 |
+
- Datasets 2.17.1
|
| 71 |
+
- Tokenizers 0.15.2
|