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synthetic-40-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: 1.3921
- Precision: 0.8929
- Recall: 0.4782
- F1 Weighted: 0.5759
- F1 Macro: 0.4410
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 |
|---|---|---|---|---|---|---|---|
| 1.0989 | 0.39 | 25 | 1.0971 | 0.6042 | 0.3430 | 0.3150 | 0.2438 |
| 0.8219 | 0.78 | 50 | 0.8525 | 0.7859 | 0.7682 | 0.7577 | 0.5881 |
| 0.5421 | 1.17 | 75 | 1.2589 | 0.8433 | 0.5047 | 0.6097 | 0.4640 |
| 0.456 | 1.56 | 100 | 1.2742 | 0.8534 | 0.5111 | 0.6086 | 0.4656 |
| 0.4956 | 1.95 | 125 | 1.4465 | 0.8210 | 0.4195 | 0.4998 | 0.3903 |
| 0.3392 | 2.34 | 150 | 1.1332 | 0.8779 | 0.5111 | 0.6126 | 0.4699 |
| 0.3776 | 2.73 | 175 | 1.3973 | 0.8858 | 0.5199 | 0.6248 | 0.4729 |
| 0.3287 | 3.12 | 200 | 1.4185 | 0.8428 | 0.5022 | 0.5984 | 0.4556 |
| 0.3325 | 3.52 | 225 | 1.3921 | 0.8929 | 0.4782 | 0.5759 | 0.4410 |
Framework versions
- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
