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xlm-roberta-base-Final_Mixed-aug_swap-2
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: 0.9261
- Accuracy: 0.76
- F1: 0.7558
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: 40
- 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 |
|---|---|---|---|---|---|
| 1.0488 | 1.0 | 87 | 0.8904 | 0.59 | 0.5101 |
| 0.8402 | 2.0 | 174 | 0.8465 | 0.64 | 0.6153 |
| 0.6864 | 3.0 | 261 | 0.7985 | 0.7 | 0.6849 |
| 0.5088 | 4.0 | 348 | 0.7521 | 0.72 | 0.6996 |
| 0.3444 | 5.0 | 435 | 0.7432 | 0.76 | 0.7496 |
| 0.262 | 6.0 | 522 | 0.8831 | 0.75 | 0.7463 |
| 0.1787 | 7.0 | 609 | 0.9219 | 0.75 | 0.7452 |
| 0.1361 | 8.0 | 696 | 0.9261 | 0.76 | 0.7558 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
