metadata
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-sentiment-b16
results: []
roberta-sentiment-b16
This model is a fine-tuned version of FacebookAI/xlm-roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8547
- F1 Macro: 0.6656
- F1 Weighted: 0.6666
- Accuracy: 0.6713
- Precision Macro: 0.6629
- Recall Macro: 0.6739
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: 16
- eval_batch_size: 16
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Weighted | Accuracy | Precision Macro | Recall Macro |
|---|---|---|---|---|---|---|---|---|
| 1.0883 | 1.0 | 241 | 0.9511 | 0.4626 | 0.4704 | 0.5317 | 0.5065 | 0.5293 |
| 0.8226 | 2.0 | 482 | 0.7453 | 0.6783 | 0.6819 | 0.6816 | 0.6879 | 0.6735 |
| 0.6465 | 3.0 | 723 | 0.7917 | 0.6843 | 0.6879 | 0.6993 | 0.6929 | 0.6948 |
| 0.5062 | 4.0 | 964 | 0.8112 | 0.6898 | 0.6922 | 0.6951 | 0.6882 | 0.6934 |
| 0.3937 | 5.0 | 1205 | 0.9096 | 0.6829 | 0.6822 | 0.6774 | 0.6989 | 0.6844 |
| 0.2821 | 6.0 | 1446 | 1.0649 | 0.6833 | 0.6861 | 0.6878 | 0.6813 | 0.6869 |
| 0.209 | 7.0 | 1687 | 1.2212 | 0.6824 | 0.6844 | 0.6826 | 0.6851 | 0.6804 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1