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synthetic-10-vsfc-xlm-r
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3908
- Precision: 0.8874
- Recall: 0.5332
- F1 Weighted: 0.6428
- F1 Macro: 0.4878
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 Weighted | F1 Macro |
|---|---|---|---|---|---|---|---|
| 1.1043 | 1.56 | 25 | 1.1570 | 0.1740 | 0.0726 | 0.0556 | 0.0633 |
| 0.9299 | 3.12 | 50 | 1.1444 | 0.6971 | 0.3696 | 0.4411 | 0.3400 |
| 0.6689 | 4.69 | 75 | 1.3908 | 0.8874 | 0.5332 | 0.6428 | 0.4878 |
Framework versions
- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
