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xlm-roberta-base-Final_Mixed-aug_delete-1
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8662
- Accuracy: 0.73
- F1: 0.7284
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: 16
- eval_batch_size: 16
- seed: 41
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.0296 | 1.0 | 88 | 0.9369 | 0.61 | 0.4985 |
| 0.8507 | 2.0 | 176 | 0.7051 | 0.72 | 0.6898 |
| 0.6817 | 3.0 | 264 | 0.6856 | 0.75 | 0.7399 |
| 0.5683 | 4.0 | 352 | 0.7131 | 0.71 | 0.6991 |
| 0.4328 | 5.0 | 440 | 0.7520 | 0.71 | 0.7119 |
| 0.3489 | 6.0 | 528 | 0.7355 | 0.72 | 0.7214 |
| 0.2746 | 7.0 | 616 | 0.8066 | 0.73 | 0.7296 |
| 0.233 | 8.0 | 704 | 0.8662 | 0.73 | 0.7284 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
