<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
xlm-roberta-large-en-si-only-finetuned-sinquad-v12
This model is a fine-tuned version of 9wimu9/xlm-roberta-large-en-si-only on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7128
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.612 | 1.0 | 93 | 0.8081 |
| 0.7979 | 2.0 | 186 | 0.6823 |
| 0.6887 | 3.0 | 279 | 0.6532 |
| 0.4166 | 4.0 | 372 | 0.6846 |
| 0.3985 | 5.0 | 465 | 0.7128 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.6.1
- Tokenizers 0.12.1
{'exact_match': 69.58841463414635, 'f1': 87.9274817360267}
