End of training

README.md

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+---
+license: bsd-3-clause
+base_model: Salesforce/codet5p-770m
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: Salesforce-codet5p-770m-finetuned-defect-cwe-group
+  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. -->
+
+# Salesforce-codet5p-770m-finetuned-defect-cwe-group
+
+This model is a fine-tuned version of [Salesforce/codet5p-770m](https://huggingface.co/Salesforce/codet5p-770m) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5725
+- Accuracy: 0.7760
+- Precision: 0.6093
+- Recall: 0.5124
+
+## 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: 4711
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|
+| No log        | 1.0   | 462  | 0.6359          | 0.7124   | 0.5669    | 0.4538 |
+| 0.7472        | 2.0   | 925  | 0.5540          | 0.7496   | 0.6085    | 0.4692 |
+| 0.5458        | 3.0   | 1387 | 0.5520          | 0.7490   | 0.5918    | 0.5082 |
+| 0.4192        | 4.0   | 1850 | 0.5505          | 0.7558   | 0.5904    | 0.5231 |
+| 0.3356        | 4.99  | 2310 | 0.5725          | 0.7760   | 0.6093    | 0.5124 |
+
+
+### Framework versions
+
+- Transformers 4.38.1
+- Pytorch 2.2.1+cu121
+- Datasets 2.17.1
+- Tokenizers 0.15.2

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