metadata
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: academic_main_text_classifier_de
results: []
academic_main_text_classifier_de
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2714
- Accuracy: 0.9193
- Precision: 0.9193
- Recall: 0.9193
- F1: 0.9193
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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch_fused 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: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 134 | 0.7912 | 0.7189 | 0.7189 | 0.7189 | 0.7189 |
| 1.0163 | 2.0 | 268 | 0.4568 | 0.8517 | 0.8517 | 0.8517 | 0.8517 |
| 0.5157 | 3.0 | 402 | 0.3827 | 0.8704 | 0.8704 | 0.8704 | 0.8704 |
| 0.5157 | 4.0 | 536 | 0.2817 | 0.9100 | 0.9100 | 0.9100 | 0.9100 |
| 0.3219 | 5.0 | 670 | 0.2714 | 0.9193 | 0.9193 | 0.9193 | 0.9193 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.9.0+cu128
- Datasets 4.2.0
- Tokenizers 0.22.1