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xlm-roberta-base-Final_Mixed-aug_delete-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: 1.0099
- Accuracy: 0.73
- F1: 0.7229
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 |
|---|---|---|---|---|---|
| 1.0876 | 1.0 | 88 | 0.9417 | 0.64 | 0.5555 |
| 0.7783 | 2.0 | 176 | 0.6350 | 0.75 | 0.7438 |
| 0.6105 | 3.0 | 264 | 0.6146 | 0.76 | 0.7570 |
| 0.4745 | 4.0 | 352 | 0.7079 | 0.75 | 0.7424 |
| 0.364 | 5.0 | 440 | 0.8401 | 0.74 | 0.7330 |
| 0.2659 | 6.0 | 528 | 0.9776 | 0.71 | 0.6996 |
| 0.2237 | 7.0 | 616 | 0.9786 | 0.74 | 0.7343 |
| 0.1594 | 8.0 | 704 | 1.0099 | 0.73 | 0.7229 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
