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xlm-roberta-base-Balance_Mixed-aug_replace_w2v
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: 1.0254
- Accuracy: 0.73
- F1: 0.7323
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 |
|---|---|---|---|---|---|
| 1.0244 | 1.0 | 84 | 0.7796 | 0.67 | 0.5775 |
| 0.839 | 2.0 | 168 | 0.8532 | 0.59 | 0.5359 |
| 0.6971 | 3.0 | 252 | 0.5937 | 0.75 | 0.7545 |
| 0.5019 | 4.0 | 336 | 0.8019 | 0.72 | 0.7120 |
| 0.3813 | 5.0 | 420 | 0.8610 | 0.73 | 0.7305 |
| 0.3196 | 6.0 | 504 | 0.8412 | 0.73 | 0.7371 |
| 0.2427 | 7.0 | 588 | 0.9769 | 0.7 | 0.7036 |
| 0.1731 | 8.0 | 672 | 1.0254 | 0.73 | 0.7323 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
