metadata
library_name: transformers
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
model-index:
- name: Tokenization-large
results: []
Tokenization-large
This model is a fine-tuned version of xlm-roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7947
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: 32
- 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 |
|---|---|---|---|
| 1.1853 | 1.0 | 14289 | 0.9966 |
| 0.9826 | 2.0 | 28578 | 0.8565 |
| 0.8465 | 3.0 | 42867 | 0.7947 |
Framework versions
- Transformers 4.56.0
- Pytorch 2.8.0+cu129
- Datasets 5.0.0
- Tokenizers 0.22.0