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xlm-roberta-base-Final_Mixed-train
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: 0.7771
- Accuracy: 0.74
- F1: 0.7319
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 |
|---|---|---|---|---|---|
| 1.1097 | 1.0 | 44 | 1.0888 | 0.38 | 0.2093 |
| 0.9875 | 2.0 | 88 | 0.8994 | 0.58 | 0.4750 |
| 0.866 | 3.0 | 132 | 0.7626 | 0.66 | 0.6018 |
| 0.7168 | 4.0 | 176 | 0.7479 | 0.65 | 0.6176 |
| 0.6423 | 5.0 | 220 | 0.7028 | 0.68 | 0.6698 |
| 0.527 | 6.0 | 264 | 0.6903 | 0.7 | 0.6939 |
| 0.4225 | 7.0 | 308 | 0.7736 | 0.67 | 0.6375 |
| 0.3765 | 8.0 | 352 | 0.7771 | 0.74 | 0.7319 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.0
- Datasets 2.14.4
- Tokenizers 0.13.3
