metadata
library_name: transformers
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: xlm-roberta-base-ibo-finetuned
results: []
xlm-roberta-base-ibo-finetuned
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3021
- F1: 0.4617
- Roc Auc: 0.6940
- Accuracy: 0.5031
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: 32
- eval_batch_size: 32
- 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: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.3848 | 1.0 | 123 | 0.3784 | 0.0 | 0.5 | 0.2150 |
| 0.3508 | 2.0 | 246 | 0.3389 | 0.1062 | 0.5434 | 0.2839 |
| 0.3227 | 3.0 | 369 | 0.3153 | 0.1134 | 0.5500 | 0.2881 |
| 0.296 | 4.0 | 492 | 0.3016 | 0.2634 | 0.6048 | 0.4134 |
| 0.2532 | 5.0 | 615 | 0.2942 | 0.3046 | 0.6338 | 0.4572 |
| 0.2297 | 6.0 | 738 | 0.2838 | 0.3835 | 0.6544 | 0.4718 |
| 0.2053 | 7.0 | 861 | 0.2839 | 0.4320 | 0.6687 | 0.4885 |
| 0.1829 | 8.0 | 984 | 0.3069 | 0.4314 | 0.6773 | 0.4948 |
| 0.1641 | 9.0 | 1107 | 0.3094 | 0.4295 | 0.6780 | 0.4802 |
| 0.1532 | 10.0 | 1230 | 0.3021 | 0.4617 | 0.6940 | 0.5031 |
| 0.1351 | 11.0 | 1353 | 0.3178 | 0.4432 | 0.6827 | 0.4843 |
| 0.1288 | 12.0 | 1476 | 0.3184 | 0.4335 | 0.6737 | 0.4843 |
| 0.1106 | 13.0 | 1599 | 0.3211 | 0.4530 | 0.6829 | 0.4760 |
| 0.113 | 14.0 | 1722 | 0.3320 | 0.4437 | 0.6815 | 0.4781 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0