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20230928-8-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: 0.4880
- 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 |
---|---|---|---|---|
4.3143 | 0.46 | 200 | 0.3054 | 4.1884 |
4.0232 | 0.91 | 400 | 0.3790 | 3.4612 |
3.8668 | 1.37 | 600 | 0.3525 | 3.5908 |
3.7855 | 1.82 | 800 | 0.4058 | nan |
3.58 | 2.28 | 1000 | 0.3795 | nan |
3.3848 | 2.73 | 1200 | 0.4046 | nan |
3.2678 | 3.19 | 1400 | 0.4439 | 3.1686 |
3.3909 | 3.64 | 1600 | 0.4248 | nan |
3.2549 | 4.1 | 1800 | 0.4460 | nan |
3.1552 | 4.56 | 2000 | 0.5051 | 2.5496 |
3.1933 | 5.01 | 2200 | 0.4706 | nan |
2.9075 | 5.47 | 2400 | 0.5124 | 2.8447 |
3.0546 | 5.92 | 2600 | 0.5136 | nan |
2.9636 | 6.38 | 2800 | 0.4931 | 2.7494 |
2.9684 | 6.83 | 3000 | 0.4962 | nan |
2.8127 | 7.29 | 3200 | 0.5077 | 2.5534 |
2.8798 | 7.74 | 3400 | 0.4961 | 2.8044 |
2.7446 | 8.2 | 3600 | 0.5071 | 2.7707 |
2.7827 | 8.66 | 3800 | 0.4919 | nan |
2.732 | 9.11 | 4000 | 0.4897 | 2.4495 |
2.7996 | 9.57 | 4200 | 0.4880 | nan |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3