| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: xlm-roberta-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: trigger-event-classifier |
| | 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. --> |
| |
|
| | # trigger-event-classifier |
| |
|
| | This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4945 |
| | - Accuracy: 0.8953 |
| |
|
| | ## 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: 2e-05 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | No log | 1.0 | 268 | 0.4588 | 0.8327 | |
| | | 0.8036 | 2.0 | 536 | 0.3313 | 0.8916 | |
| | | 0.8036 | 3.0 | 804 | 0.3508 | 0.8794 | |
| | | 0.2874 | 4.0 | 1072 | 0.3391 | 0.8972 | |
| | | 0.2874 | 5.0 | 1340 | 0.3871 | 0.8916 | |
| | | 0.2051 | 6.0 | 1608 | 0.4519 | 0.8907 | |
| | | 0.2051 | 7.0 | 1876 | 0.4365 | 0.8935 | |
| | | 0.1614 | 8.0 | 2144 | 0.4362 | 0.9 | |
| | | 0.1614 | 9.0 | 2412 | 0.5012 | 0.8953 | |
| | | 0.1204 | 10.0 | 2680 | 0.4945 | 0.8953 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.53.1 |
| | - Pytorch 2.7.1+cu126 |
| | - Datasets 3.6.0 |
| | - Tokenizers 0.21.2 |
| |
|
