metadata
library_name: transformers
license: mit
base_model: PracticalWork/xlm-roberta-large-classifier
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-large-classifier-classifier-prompted
results: []
xlm-roberta-large-classifier-classifier-prompted
This model is a fine-tuned version of PracticalWork/xlm-roberta-large-classifier on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3406
- Accuracy: 0.8891
- F1: 0.8898
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: 32
- eval_batch_size: 32
- 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 | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 0 | 0 | 0.8239 | 0.7029 | 0.6341 |
| No log | 0.6 | 255 | 0.3202 | 0.8832 | 0.8681 |
| 0.3462 | 1.2 | 510 | 0.2943 | 0.8827 | 0.8824 |
| 0.3462 | 1.8 | 765 | 0.2771 | 0.8967 | 0.8942 |
| 0.2258 | 2.4 | 1020 | 0.3878 | 0.8768 | 0.8796 |
| 0.2258 | 3.0 | 1275 | 0.3406 | 0.8891 | 0.8898 |
Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1