| --- |
| base_model: cardiffnlp/twitter-xlm-roberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: training_with_callbacks |
| 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. --> |
|
|
| # training_with_callbacks |
|
|
| This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4317 |
| - Precision: 0.7304 |
| - Recall: 0.7613 |
| - F1: 0.7456 |
|
|
| ## 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: 32 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 50 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:| |
| | No log | 1.0 | 458 | 0.4317 | 0.7304 | 0.7613 | 0.7456 | |
| | 0.5107 | 2.0 | 916 | 0.4730 | 0.8008 | 0.6193 | 0.6985 | |
| | 0.3555 | 3.0 | 1374 | 0.4850 | 0.7512 | 0.7205 | 0.7355 | |
| | 0.2265 | 4.0 | 1832 | 0.6697 | 0.7379 | 0.7356 | 0.7368 | |
| | 0.1547 | 5.0 | 2290 | 0.7118 | 0.7491 | 0.6450 | 0.6932 | |
| | 0.1154 | 6.0 | 2748 | 1.0137 | 0.7177 | 0.7221 | 0.7199 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.41.2 |
| - Pytorch 2.3.0+cu121 |
| - Datasets 2.19.2 |
| - Tokenizers 0.19.1 |
|
|
