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xlm-roberta-base-finetuned-non-code-mixed-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: 1.1771
- Accuracy: 0.6365
- Precision: 0.6252
- Recall: 0.6242
- F1: 0.6242
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 |
|---|---|---|---|---|---|---|---|
| 0.9475 | 2.0 | 926 | 0.8620 | 0.6278 | 0.6197 | 0.6042 | 0.6081 |
| 0.6661 | 3.99 | 1852 | 0.9578 | 0.6451 | 0.6356 | 0.6281 | 0.6301 |
| 0.4457 | 5.99 | 2778 | 1.1771 | 0.6365 | 0.6252 | 0.6242 | 0.6242 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.10.1+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1
