| | --- |
| | library_name: peft |
| | tags: |
| | - parquet |
| | - text-classification |
| | datasets: |
| | - tweet_eval |
| | metrics: |
| | - accuracy |
| | base_model: mrm8488/codebert-base-finetuned-detect-insecure-code |
| | model-index: |
| | - name: mrm8488_codebert-base-finetuned-detect-insecure-code-finetuned-lora-tweet_eval_hate |
| | results: |
| | - task: |
| | type: text-classification |
| | name: Text Classification |
| | dataset: |
| | name: tweet_eval |
| | type: tweet_eval |
| | config: hate |
| | split: validation |
| | args: hate |
| | metrics: |
| | - type: accuracy |
| | value: 0.703 |
| | name: accuracy |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # mrm8488_codebert-base-finetuned-detect-insecure-code-finetuned-lora-tweet_eval_hate |
| | |
| | This model is a fine-tuned version of [mrm8488/codebert-base-finetuned-detect-insecure-code](https://huggingface.co/mrm8488/codebert-base-finetuned-detect-insecure-code) on the tweet_eval dataset. |
| | It achieves the following results on the evaluation set: |
| | - accuracy: 0.703 |
| |
|
| | ## 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: 0.0004 |
| | - train_batch_size: 32 |
| | - eval_batch_size: 32 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 4 |
| |
|
| | ### Training results |
| |
|
| | | accuracy | train_loss | epoch | |
| | |:--------:|:----------:|:-----:| |
| | | 0.497 | None | 0 | |
| | | 0.704 | 0.6110 | 0 | |
| | | 0.694 | 0.5496 | 1 | |
| | | 0.694 | 0.5181 | 2 | |
| | | 0.703 | 0.5022 | 3 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - PEFT 0.8.2 |
| | - Transformers 4.37.2 |
| | - Pytorch 2.2.0 |
| | - Datasets 2.16.1 |
| | - Tokenizers 0.15.2 |
