<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
xlm-roberta-base-Final_Mixed-aug_replace_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: 1.0103
- Accuracy: 0.75
- F1: 0.7433
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 |
|---|---|---|---|---|---|
| 1.0863 | 1.0 | 86 | 0.8715 | 0.59 | 0.5464 |
| 0.8221 | 2.0 | 172 | 0.6132 | 0.72 | 0.7008 |
| 0.6363 | 3.0 | 258 | 0.6041 | 0.72 | 0.7189 |
| 0.5206 | 4.0 | 344 | 0.7012 | 0.73 | 0.7224 |
| 0.3526 | 5.0 | 430 | 0.8181 | 0.75 | 0.7468 |
| 0.2893 | 6.0 | 516 | 0.7950 | 0.77 | 0.7690 |
| 0.2097 | 7.0 | 602 | 0.9751 | 0.74 | 0.7335 |
| 0.1536 | 8.0 | 688 | 1.0103 | 0.75 | 0.7433 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
