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xlm-roberta-base-Final_Mixed-aug_insert_w2v-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: 1.2389
- Accuracy: 0.77
- F1: 0.7662
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 |
|---|---|---|---|---|---|
| 1.054 | 1.0 | 86 | 0.8403 | 0.68 | 0.6696 |
| 0.7333 | 2.0 | 172 | 0.5967 | 0.76 | 0.7598 |
| 0.5218 | 3.0 | 258 | 0.6397 | 0.77 | 0.7688 |
| 0.3402 | 4.0 | 344 | 0.7154 | 0.79 | 0.7825 |
| 0.232 | 5.0 | 430 | 0.8591 | 0.76 | 0.7586 |
| 0.1443 | 6.0 | 516 | 1.0384 | 0.78 | 0.7774 |
| 0.1122 | 7.0 | 602 | 1.1989 | 0.76 | 0.7566 |
| 0.0917 | 8.0 | 688 | 1.2389 | 0.77 | 0.7662 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
