roberta-finetuned-ner-nergrit-8H
This model is a fine-tuned version of FacebookAI/xlm-roberta-large on the nergrit dataset. It achieves the following results on the evaluation set:
- Loss: 0.0956
- Precision: 0.9847
- Recall: 0.9845
- F1: 0.9846
- Accuracy: 0.9811
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- 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 |
---|---|---|---|---|---|---|---|
No log | 0.9995 | 471 | 0.0984 | 0.9819 | 0.9822 | 0.9820 | 0.9782 |
0.1862 | 1.9989 | 942 | 0.0940 | 0.9848 | 0.9834 | 0.9841 | 0.9802 |
0.0843 | 2.9984 | 1413 | 0.0956 | 0.9847 | 0.9845 | 0.9846 | 0.9811 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for mufathurrohman/roberta-finetuned-ner-nergrit-8H
Base model
FacebookAI/xlm-roberta-largeEvaluation results
- Precision on nergrittest set self-reported0.985
- Recall on nergrittest set self-reported0.985
- F1 on nergrittest set self-reported0.985
- Accuracy on nergrittest set self-reported0.981