20230928-1-xlm-roberta-base-new
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Accuracy: 0.4663
- Loss: 2.7549
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|---|---|---|---|---|
| 4.5242 | 0.46 | 200 | 0.3115 | 3.6451 |
| 4.0841 | 0.91 | 400 | 0.3325 | 3.4312 |
| 3.7774 | 1.37 | 600 | 0.3357 | nan |
| 3.7354 | 1.82 | 800 | 0.38 | nan |
| 3.586 | 2.28 | 1000 | 0.3763 | 3.3689 |
| 3.51 | 2.73 | 1200 | 0.4209 | nan |
| 3.4578 | 3.19 | 1400 | 0.4132 | 3.0195 |
| 3.2155 | 3.64 | 1600 | 0.4455 | 3.2697 |
| 3.1555 | 4.1 | 1800 | 0.4660 | nan |
| 3.0647 | 4.56 | 2000 | 0.4244 | 2.6126 |
| 3.1005 | 5.01 | 2200 | 0.4344 | nan |
| 3.0598 | 5.47 | 2400 | 0.4928 | 2.5990 |
| 3.032 | 5.92 | 2600 | 0.5036 | 2.6536 |
| 2.9123 | 6.38 | 2800 | 0.5025 | 2.7367 |
| 3.0423 | 6.83 | 3000 | 0.4803 | 2.8070 |
| 2.7696 | 7.29 | 3200 | 0.4973 | nan |
| 2.7321 | 7.74 | 3400 | 0.5105 | 2.8622 |
| 2.8714 | 8.2 | 3600 | 0.4936 | 2.5544 |
| 2.8736 | 8.66 | 3800 | 0.5274 | 2.5878 |
| 2.779 | 9.11 | 4000 | 0.5219 | nan |
| 2.6934 | 9.57 | 4200 | 0.4663 | 2.7549 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3