tmp
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6486
- Precision: 0.6540
- Recall: 0.6944
- F1: 0.6736
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|---|---|---|---|---|---|---|
| No log | 1.0 | 38 | 0.7892 | 0.5800 | 0.6787 | 0.6255 |
| No log | 2.0 | 76 | 0.5906 | 0.7267 | 0.7540 | 0.7401 |
| No log | 3.0 | 114 | 0.5466 | 0.7219 | 0.7771 | 0.7485 |
| No log | 4.0 | 152 | 0.5249 | 0.7266 | 0.7623 | 0.7440 |
| No log | 5.0 | 190 | 0.5261 | 0.7228 | 0.7674 | 0.7445 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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Base model
FacebookAI/xlm-roberta-base