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20230928-9-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: 0.5108
- 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 |
|---|---|---|---|---|
| 4.5519 | 0.46 | 200 | 0.2982 | nan |
| 4.1573 | 0.91 | 400 | 0.3194 | nan |
| 3.8898 | 1.37 | 600 | 0.3280 | nan |
| 3.7149 | 1.82 | 800 | 0.3765 | 3.2017 |
| 3.5722 | 2.28 | 1000 | 0.4056 | nan |
| 3.4367 | 2.73 | 1200 | 0.3648 | 3.0582 |
| 3.3854 | 3.19 | 1400 | 0.3741 | nan |
| 3.4153 | 3.64 | 1600 | 0.4019 | 2.8494 |
| 3.3047 | 4.1 | 1800 | 0.4049 | 2.9662 |
| 3.1112 | 4.56 | 2000 | 0.4419 | 3.0672 |
| 3.3055 | 5.01 | 2200 | 0.4746 | 2.9201 |
| 2.948 | 5.47 | 2400 | 0.4633 | nan |
| 2.9887 | 5.92 | 2600 | 0.4349 | 2.9944 |
| 2.9127 | 6.38 | 2800 | 0.4832 | 2.5580 |
| 2.7644 | 6.83 | 3000 | 0.4737 | 2.6597 |
| 2.8758 | 7.29 | 3200 | 0.4226 | 3.1813 |
| 2.9334 | 7.74 | 3400 | 0.4670 | 2.5154 |
| 2.7652 | 8.2 | 3600 | 0.4860 | 2.7003 |
| 2.7986 | 8.66 | 3800 | 0.5547 | nan |
| 2.7419 | 9.11 | 4000 | 0.5095 | nan |
| 2.7937 | 9.57 | 4200 | 0.5108 | nan |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
