| --- |
| library_name: transformers |
| base_model: cardiffnlp/twitter-roberta-base-sentiment-latest |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| - precision |
| - recall |
| model-index: |
| - name: finetuning-sentiment-model-youtube-samples |
| 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. --> |
|
|
| # finetuning-sentiment-model-youtube-samples |
|
|
| This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.9901 |
| - Accuracy: 0.8418 |
| - F1: 0.8381 |
| - Precision: 0.8418 |
| - Recall: 0.8418 |
|
|
| ## 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: 32 |
| - eval_batch_size: 16 |
| - 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 |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | 0.6387 | 1.0 | 22 | 0.6277 | 0.7062 | 0.7069 | 0.7062 | 0.7062 | |
| | 0.3508 | 2.0 | 44 | 0.4970 | 0.8023 | 0.8043 | 0.8023 | 0.8023 | |
| | 0.1586 | 3.0 | 66 | 0.8574 | 0.7910 | 0.7829 | 0.7910 | 0.7910 | |
| | 0.0663 | 4.0 | 88 | 0.7822 | 0.8079 | 0.8086 | 0.8079 | 0.8079 | |
| | 0.0351 | 5.0 | 110 | 0.8371 | 0.8305 | 0.8188 | 0.8305 | 0.8305 | |
| | 0.0274 | 6.0 | 132 | 0.8634 | 0.8475 | 0.8423 | 0.8475 | 0.8475 | |
| | 0.0049 | 7.0 | 154 | 0.9682 | 0.8079 | 0.8023 | 0.8079 | 0.8079 | |
| | 0.0015 | 8.0 | 176 | 0.9604 | 0.8362 | 0.8348 | 0.8362 | 0.8362 | |
| | 0.0007 | 9.0 | 198 | 0.9754 | 0.8418 | 0.8381 | 0.8418 | 0.8418 | |
| | 0.0011 | 10.0 | 220 | 0.9901 | 0.8418 | 0.8381 | 0.8418 | 0.8418 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.2 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
