20230928-7-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: 0.4740
- Loss: nan
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 |
|---|---|---|---|---|
| 4.4628 | 0.46 | 200 | 0.3220 | nan |
| 4.1552 | 0.91 | 400 | 0.3249 | nan |
| 3.8537 | 1.37 | 600 | 0.3822 | nan |
| 3.5294 | 1.82 | 800 | 0.3914 | 3.6973 |
| 3.378 | 2.28 | 1000 | 0.3770 | 3.5247 |
| 3.3717 | 2.73 | 1200 | 0.3795 | nan |
| 3.3769 | 3.19 | 1400 | 0.4033 | 2.9623 |
| 3.2682 | 3.64 | 1600 | 0.3975 | 3.3065 |
| 3.3275 | 4.1 | 1800 | 0.4603 | 3.0879 |
| 3.1686 | 4.56 | 2000 | 0.4385 | 2.8513 |
| 3.1107 | 5.01 | 2200 | 0.4419 | nan |
| 3.0418 | 5.47 | 2400 | 0.4372 | nan |
| 2.9602 | 5.92 | 2600 | 0.4792 | 2.8451 |
| 2.9038 | 6.38 | 2800 | 0.4772 | 2.7947 |
| 2.8495 | 6.83 | 3000 | 0.415 | 2.9448 |
| 2.9444 | 7.29 | 3200 | 0.4840 | nan |
| 2.8306 | 7.74 | 3400 | 0.4806 | 2.3816 |
| 2.8293 | 8.2 | 3600 | 0.4909 | 2.8671 |
| 2.7785 | 8.66 | 3800 | 0.5377 | 2.6516 |
| 2.7991 | 9.11 | 4000 | 0.5164 | nan |
| 2.8131 | 9.57 | 4200 | 0.4740 | nan |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3