|
|
--- |
|
|
library_name: transformers |
|
|
license: mit |
|
|
base_model: xlm-roberta-base |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
- precision |
|
|
- recall |
|
|
model-index: |
|
|
- name: xlm-roberta-base-orm |
|
|
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. --> |
|
|
|
|
|
# xlm-roberta-base-orm |
|
|
|
|
|
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: 0.1489 |
|
|
- Accuracy: 0.7726 |
|
|
- F1 Binary: 0.3856 |
|
|
- Precision: 0.3070 |
|
|
- Recall: 0.5185 |
|
|
|
|
|
## 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: 3e-05 |
|
|
- train_batch_size: 32 |
|
|
- eval_batch_size: 8 |
|
|
- 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: linear |
|
|
- lr_scheduler_warmup_steps: 51 |
|
|
- num_epochs: 4 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Binary | Precision | Recall | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:---------:|:------:| |
|
|
| 0.1794 | 1.0 | 517 | 0.1732 | 0.3619 | 0.2385 | 0.1427 | 0.7258 | |
|
|
| 0.1723 | 2.0 | 1034 | 0.1690 | 0.5982 | 0.2995 | 0.1970 | 0.6239 | |
|
|
| 0.1522 | 3.0 | 1551 | 0.1818 | 0.8566 | 0.2847 | 0.4538 | 0.2074 | |
|
|
| 0.1436 | 4.0 | 2068 | 0.1489 | 0.7726 | 0.3856 | 0.3070 | 0.5185 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.48.0 |
|
|
- Pytorch 2.5.1+cu124 |
|
|
- Datasets 3.1.0 |
|
|
- Tokenizers 0.21.0 |
|
|
|
