xlm-roberta-large-tweet-sentiment-spanish-bs4
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: 1.1033
- Accuracy: 0.3885
- Precision: 0.1510
- Recall: 0.3885
- F1 Macro: 0.1865
- F1 Weighted: 0.2174
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: 4
- eval_batch_size: 4
- 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 | Accuracy | Precision | Recall | F1 Macro | F1 Weighted |
|---|---|---|---|---|---|---|---|---|
| 1.1375 | 1.0 | 391 | 1.1179 | 0.2864 | 0.0821 | 0.2864 | 0.1484 | 0.1276 |
| 1.1199 | 2.0 | 782 | 1.1043 | 0.3248 | 0.1055 | 0.3248 | 0.1634 | 0.1593 |
| 1.1158 | 3.0 | 1173 | 1.1035 | 0.3887 | 0.1511 | 0.3887 | 0.1866 | 0.2176 |
| 1.1087 | 4.0 | 1564 | 1.1160 | 0.3248 | 0.1055 | 0.3248 | 0.1634 | 0.1593 |
| 1.11 | 5.0 | 1955 | 1.0982 | 0.3887 | 0.1511 | 0.3887 | 0.1866 | 0.2176 |
| 1.1093 | 6.0 | 2346 | 1.0991 | 0.2864 | 0.0821 | 0.2864 | 0.1484 | 0.1276 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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Model tree for Moravak/xlm-roberta-large-tweet-sentiment-spanish-bs4
Base model
FacebookAI/xlm-roberta-large