| | --- |
| | license: mit |
| | library_name: peft |
| | tags: |
| | - parquet |
| | - text-classification |
| | datasets: |
| | - tweet_eval |
| | metrics: |
| | - accuracy |
| | base_model: roberta-base |
| | model-index: |
| | - name: roberta-base-finetuned-lora-tweet_eval_irony |
| | results: |
| | - task: |
| | type: text-classification |
| | name: Text Classification |
| | dataset: |
| | name: tweet_eval |
| | type: tweet_eval |
| | config: irony |
| | split: validation |
| | args: irony |
| | metrics: |
| | - type: accuracy |
| | value: 0.7329842931937173 |
| | 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. --> |
| |
|
| | # roberta-base-finetuned-lora-tweet_eval_irony |
| |
|
| | This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the tweet_eval dataset. |
| | It achieves the following results on the evaluation set: |
| | - accuracy: 0.7330 |
| | |
| | ## 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: 0.0005 |
| | - 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: 8 |
| | |
| | ### Training results |
| | |
| | | accuracy | train_loss | epoch | |
| | |:--------:|:----------:|:-----:| |
| | | 0.4775 | None | 0 | |
| | | 0.5969 | 0.6883 | 0 | |
| | | 0.6932 | 0.6138 | 1 | |
| | | 0.6942 | 0.5623 | 2 | |
| | | 0.7277 | 0.5362 | 3 | |
| | | 0.7277 | 0.5078 | 4 | |
| | | 0.7267 | 0.4934 | 5 | |
| | | 0.7298 | 0.4820 | 6 | |
| | | 0.7330 | 0.4758 | 7 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - PEFT 0.8.2 |
| | - Transformers 4.37.2 |
| | - Pytorch 2.2.0 |
| | - Datasets 2.16.1 |
| | - Tokenizers 0.15.2 |
