| --- |
| library_name: transformers |
| base_model: cardiffnlp/twitter-roberta-base-sentiment-latest |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| - precision |
| - recall |
| model-index: |
| - name: finetuning-sentiment-model-tweet-OLDsamples |
| 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-tweet-OLDsamples |
|
|
| 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: 1.3200 |
| - Accuracy Percentage: 0.7738 |
| - Accuracy Number: 65.0 |
| - F1: 0.7878 |
| - Precision: 0.7738 |
| - Recall: 0.7738 |
|
|
| ## 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 Percentage | Accuracy Number | F1 | Precision | Recall | |
| |:-------------:|:-----:|:----:|:---------------:|:-------------------:|:---------------:|:------:|:---------:|:------:| |
| | 0.5465 | 1.0 | 11 | 0.5817 | 0.7857 | 66.0 | 0.7854 | 0.7857 | 0.7857 | |
| | 0.351 | 2.0 | 22 | 0.4817 | 0.7976 | 67.0 | 0.7930 | 0.7976 | 0.7976 | |
| | 0.1612 | 3.0 | 33 | 1.0279 | 0.75 | 63.0 | 0.7618 | 0.75 | 0.75 | |
| | 0.0734 | 4.0 | 44 | 1.0266 | 0.7857 | 66.0 | 0.7968 | 0.7857 | 0.7857 | |
| | 0.0303 | 5.0 | 55 | 0.8942 | 0.8095 | 68.0 | 0.8150 | 0.8095 | 0.8095 | |
| | 0.0083 | 6.0 | 66 | 1.1278 | 0.8095 | 68.0 | 0.8177 | 0.8095 | 0.8095 | |
| | 0.0028 | 7.0 | 77 | 1.2560 | 0.7738 | 65.0 | 0.7878 | 0.7738 | 0.7738 | |
| | 0.0012 | 8.0 | 88 | 1.2988 | 0.7738 | 65.0 | 0.7878 | 0.7738 | 0.7738 | |
| | 0.001 | 9.0 | 99 | 1.3170 | 0.7857 | 66.0 | 0.7997 | 0.7857 | 0.7857 | |
| | 0.001 | 10.0 | 110 | 1.3200 | 0.7738 | 65.0 | 0.7878 | 0.7738 | 0.7738 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.2 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
