xlm-roberta-base-20240102
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1715
- F1: 0.7601
- Roc Auc: 0.8408
- Accuracy: 0.7024
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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
---|---|---|---|---|---|---|
No log | 1.0 | 109 | 0.2679 | 0.32 | 0.5957 | 0.1938 |
No log | 2.0 | 218 | 0.2054 | 0.6377 | 0.7490 | 0.5111 |
No log | 3.0 | 327 | 0.1897 | 0.7162 | 0.7956 | 0.6026 |
No log | 4.0 | 436 | 0.1776 | 0.7531 | 0.8345 | 0.6891 |
0.2255 | 5.0 | 545 | 0.1715 | 0.7601 | 0.8408 | 0.7024 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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