---
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   |


### Framework versions

- Transformers 4.53.1
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.2