metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: xlm_roberta_kriter
results: []
xlm_roberta_kriter
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: 0.1944
- F1: 0.7931
- Roc Auc: 0.8977
- Accuracy: 0.7656
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.3583 | 1.0 | 1151 | 0.3227 | 0.1209 | 0.5303 | 0.4766 |
| 0.289 | 2.0 | 2302 | 0.2266 | 0.6301 | 0.7660 | 0.6719 |
| 0.214 | 3.0 | 3453 | 0.1938 | 0.7500 | 0.8319 | 0.7344 |
| 0.1901 | 4.0 | 4604 | 0.1990 | 0.7328 | 0.8522 | 0.7188 |
| 0.1646 | 5.0 | 5755 | 0.1865 | 0.7664 | 0.8626 | 0.7344 |
| 0.1507 | 6.0 | 6906 | 0.1760 | 0.8030 | 0.8955 | 0.7773 |
| 0.1247 | 7.0 | 8057 | 0.1797 | 0.8010 | 0.9033 | 0.7695 |
| 0.1084 | 8.0 | 9208 | 0.1869 | 0.8051 | 0.8918 | 0.7812 |
| 0.0767 | 9.0 | 10359 | 0.1942 | 0.7931 | 0.8977 | 0.7617 |
| 0.0796 | 10.0 | 11510 | 0.1944 | 0.7931 | 0.8977 | 0.7656 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1