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xlm-roberta-base-Final_Mixed-aug_insert_tfidf-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: 1.1653
- Accuracy: 0.73
- F1: 0.7222
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 |
|---|---|---|---|---|---|
| 1.0021 | 1.0 | 88 | 0.7305 | 0.7 | 0.6605 |
| 0.727 | 2.0 | 176 | 0.6881 | 0.73 | 0.7211 |
| 0.5792 | 3.0 | 264 | 0.7957 | 0.75 | 0.7438 |
| 0.4195 | 4.0 | 352 | 0.9646 | 0.73 | 0.7207 |
| 0.2877 | 5.0 | 440 | 0.9529 | 0.72 | 0.7095 |
| 0.2378 | 6.0 | 528 | 1.0659 | 0.75 | 0.7434 |
| 0.1856 | 7.0 | 616 | 1.1323 | 0.73 | 0.7236 |
| 0.1353 | 8.0 | 704 | 1.1653 | 0.73 | 0.7222 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
