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xlm-roberta-base-Final_Mixed-aug_replace_BERT-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: 0.7460
- Accuracy: 0.75
- F1: 0.7473
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 |
|---|---|---|---|---|---|
| 1.0554 | 1.0 | 88 | 0.9377 | 0.5 | 0.4177 |
| 0.8929 | 2.0 | 176 | 0.8133 | 0.64 | 0.5654 |
| 0.7778 | 3.0 | 264 | 0.6756 | 0.73 | 0.7154 |
| 0.6686 | 4.0 | 352 | 0.6923 | 0.75 | 0.7378 |
| 0.5672 | 5.0 | 440 | 0.6880 | 0.77 | 0.7706 |
| 0.5009 | 6.0 | 528 | 0.7243 | 0.77 | 0.7668 |
| 0.3978 | 7.0 | 616 | 0.7148 | 0.76 | 0.7584 |
| 0.3843 | 8.0 | 704 | 0.7460 | 0.75 | 0.7473 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
