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20230928-5-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: 0.5236
- 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 |
|---|---|---|---|---|
| 4.5001 | 0.46 | 200 | 0.2965 | nan |
| 4.0546 | 0.91 | 400 | 0.3261 | 3.5917 |
| 3.7694 | 1.37 | 600 | 0.3403 | nan |
| 3.6655 | 1.82 | 800 | 0.2936 | nan |
| 3.5615 | 2.28 | 1000 | 0.3601 | 3.3849 |
| 3.3854 | 2.73 | 1200 | 0.4212 | 3.2257 |
| 3.321 | 3.19 | 1400 | 0.4053 | nan |
| 3.3052 | 3.64 | 1600 | 0.4615 | nan |
| 3.1626 | 4.1 | 1800 | 0.4169 | 2.8506 |
| 3.1598 | 4.56 | 2000 | 0.4441 | 2.8069 |
| 3.0887 | 5.01 | 2200 | 0.4215 | 3.0388 |
| 3.0471 | 5.47 | 2400 | 0.4562 | 2.8999 |
| 3.0477 | 5.92 | 2600 | 0.4587 | 2.8482 |
| 2.6846 | 6.38 | 2800 | 0.4778 | 2.6451 |
| 2.9033 | 6.83 | 3000 | 0.4688 | 2.5056 |
| 2.9835 | 7.29 | 3200 | 0.4794 | 2.7805 |
| 2.8992 | 7.74 | 3400 | 0.5 | 2.7021 |
| 2.8387 | 8.2 | 3600 | 0.5176 | nan |
| 2.8935 | 8.66 | 3800 | 0.4929 | nan |
| 2.7382 | 9.11 | 4000 | 0.4913 | nan |
| 2.8238 | 9.57 | 4200 | 0.5236 | nan |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
