my_xlm-roberta-large-finetuned-conll03
This model is a fine-tuned version of xlm-roberta-large on the conll2003 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1185
- Precision: 0.9244
- Recall: 0.9375
- F1: 0.9309
- Accuracy: 0.9856
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.1533 | 1.0 | 878 | 0.1178 | 0.8950 | 0.9053 | 0.9001 | 0.9805 |
0.0303 | 2.0 | 1756 | 0.1157 | 0.9157 | 0.9331 | 0.9243 | 0.9843 |
0.0164 | 3.0 | 2634 | 0.1185 | 0.9244 | 0.9375 | 0.9309 | 0.9856 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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Model tree for BahAdoR0101/my_xlm-roberta-large-finetuned-conll03
Base model
FacebookAI/xlm-roberta-largeDataset used to train BahAdoR0101/my_xlm-roberta-large-finetuned-conll03
Evaluation results
- Precision on conll2003test set self-reported0.924
- Recall on conll2003test set self-reported0.938
- F1 on conll2003test set self-reported0.931
- Accuracy on conll2003test set self-reported0.986