xlm-roberta-large
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0004
- Precision: 0.9778
- Recall: 0.9913
- F1: 0.9845
- Accuracy: 0.9999
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.0012 | 1.0 | 2292 | 0.0007 | 0.9427 | 0.9777 | 0.9599 | 0.9998 |
0.0006 | 2.0 | 4584 | 0.0006 | 0.9664 | 0.9863 | 0.9762 | 0.9998 |
0.0003 | 3.0 | 6876 | 0.0004 | 0.9778 | 0.9913 | 0.9845 | 0.9999 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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