metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: fine-tuned-NLI-multilingual-with-xlm-roberta-large
results: []
fine-tuned-NLI-multilingual-with-xlm-roberta-large
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: 0.4158
- Accuracy: 0.8600
- F1: 0.8612
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
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Accuracy | F1 | Validation Loss |
|---|---|---|---|---|---|
| 0.4647 | 0.5 | 1613 | 0.8396 | 0.8403 | 0.4262 |
| 0.4437 | 1.0 | 3226 | 0.8511 | 0.8522 | 0.4042 |
| 0.3956 | 1.5 | 4839 | 0.3783 | 0.8604 | 0.8602 |
| 0.3639 | 2.0 | 6452 | 0.3913 | 0.8592 | 0.8600 |
| 0.323 | 2.5 | 8065 | 0.3783 | 0.8657 | 0.8659 |
| 0.3186 | 3.0 | 9678 | 0.3850 | 0.8626 | 0.8625 |
| 0.2485 | 3.5 | 11291 | 0.4326 | 0.8597 | 0.8592 |
| 0.2509 | 4.0 | 12904 | 0.4158 | 0.8600 | 0.8612 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.3