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20230928-3-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: 0.5422
- Loss: 2.4161
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 |
|---|---|---|---|---|
| 4.4417 | 0.46 | 200 | 0.2696 | nan |
| 4.0961 | 0.91 | 400 | 0.3189 | nan |
| 3.7075 | 1.37 | 600 | 0.3422 | nan |
| 3.6918 | 1.82 | 800 | 0.3297 | 3.6692 |
| 3.7041 | 2.28 | 1000 | 0.4063 | 3.5981 |
| 3.4991 | 2.73 | 1200 | 0.4211 | 2.8302 |
| 3.3064 | 3.19 | 1400 | 0.4413 | 2.8908 |
| 3.3633 | 3.64 | 1600 | 0.3834 | nan |
| 3.2069 | 4.1 | 1800 | 0.4505 | nan |
| 3.1465 | 4.56 | 2000 | 0.4263 | 2.9270 |
| 3.1135 | 5.01 | 2200 | 0.4654 | nan |
| 3.0798 | 5.47 | 2400 | 0.4667 | 2.8386 |
| 3.0095 | 5.92 | 2600 | 0.4212 | 3.0044 |
| 2.9742 | 6.38 | 2800 | 0.4704 | nan |
| 2.968 | 6.83 | 3000 | 0.4883 | 2.3328 |
| 2.8909 | 7.29 | 3200 | 0.4935 | nan |
| 2.9974 | 7.74 | 3400 | 0.4185 | nan |
| 2.7729 | 8.2 | 3600 | 0.5163 | 2.4607 |
| 2.784 | 8.66 | 3800 | 0.4840 | 2.5350 |
| 2.7778 | 9.11 | 4000 | 0.5251 | nan |
| 2.7316 | 9.57 | 4200 | 0.5422 | 2.4161 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
