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xlm-roberta-base-finetuned-ours-DS
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: 0.9899
- Accuracy: 0.725
- Precision: 0.6875
- Recall: 0.6723
- F1: 0.6779
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: 1.6820964947491663e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 43
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
0.9962 | 1.99 | 199 | 0.8025 | 0.59 | 0.6055 | 0.5507 | 0.4746 |
0.6724 | 3.98 | 398 | 0.8205 | 0.705 | 0.6678 | 0.6520 | 0.6492 |
0.4259 | 5.97 | 597 | 0.9899 | 0.725 | 0.6875 | 0.6723 | 0.6779 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.10.1+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1