metadata
library_name: transformers
base_model: cardiffnlp/twitter-xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: multipride_xml_roberta
results: []
multipride_xml_roberta
This model is a fine-tuned version of cardiffnlp/twitter-xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3575
- Accuracy: 0.9018
- Precision: 0.8201
- Recall: 0.7409
- F1: 0.7720
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.3699 | 1.0 | 262 | 0.3192 | 0.8906 | 0.9149 | 0.6237 | 0.6675 |
| 0.306 | 2.0 | 524 | 0.3669 | 0.8973 | 0.8080 | 0.7318 | 0.7616 |
| 0.2227 | 3.0 | 786 | 0.3575 | 0.9018 | 0.8201 | 0.7409 | 0.7720 |
Framework versions
- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1