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xlm-roberta-base-Balance_Mixed-aug_insert
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: 1.8765
- Accuracy: 0.68
- F1: 0.6779
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: 42
- 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 |
|---|---|---|---|---|---|
| 0.9796 | 1.0 | 87 | 0.7820 | 0.65 | 0.6411 |
| 0.6824 | 2.0 | 174 | 0.5968 | 0.67 | 0.6578 |
| 0.5057 | 3.0 | 261 | 0.8463 | 0.69 | 0.6620 |
| 0.3193 | 4.0 | 348 | 0.9758 | 0.71 | 0.6991 |
| 0.1899 | 5.0 | 435 | 1.4013 | 0.67 | 0.6711 |
| 0.116 | 6.0 | 522 | 1.5033 | 0.71 | 0.7069 |
| 0.0823 | 7.0 | 609 | 1.7558 | 0.69 | 0.6864 |
| 0.0627 | 8.0 | 696 | 1.8765 | 0.68 | 0.6779 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
