metadata
library_name: transformers
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: xlm-roberta-sentiment-batch-4
results: []
xlm-roberta-sentiment-batch-4
This model is a fine-tuned version of xlm-roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0996
- F1 Macro: 0.1868
- F1 Weighted: 0.2182
- Accuracy: 0.3893
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: 3e-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
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Weighted | Accuracy |
|---|---|---|---|---|---|---|
| 1.1229 | 1.0 | 1201 | 1.1017 | 0.1868 | 0.2182 | 0.3893 |
| 1.1194 | 2.0 | 2402 | 1.1030 | 0.1634 | 0.1591 | 0.3246 |
| 1.0971 | 3.0 | 3603 | 1.1045 | 0.1634 | 0.1591 | 0.3246 |
| 1.1134 | 4.0 | 4804 | 1.0996 | 0.1868 | 0.2182 | 0.3893 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1