roberta-finetuned-ner-nergrit-8H-light
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: 0.1130
- Precision: 0.9810
- Recall: 0.9811
- F1: 0.9810
- Accuracy: 0.9773
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 | 0.9994 | 392 | 0.1196 | 0.9793 | 0.9800 | 0.9796 | 0.9757 |
0.1919 | 1.9987 | 784 | 0.1048 | 0.9810 | 0.9814 | 0.9812 | 0.9775 |
0.0823 | 2.9981 | 1176 | 0.1130 | 0.9810 | 0.9811 | 0.9810 | 0.9773 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Downloads last month
- 0
Model tree for mufathurrohman/roberta-finetuned-ner-nergrit-8H-light
Base model
FacebookAI/xlm-roberta-largeEvaluation results
- Precision on nergritvalidation set self-reported0.981
- Recall on nergritvalidation set self-reported0.981
- F1 on nergritvalidation set self-reported0.981
- Accuracy on nergritvalidation set self-reported0.977