wikineural-multilingual-ner-finetuned-ner
This model is a fine-tuned version of Babelscape/wikineural-multilingual-ner on the skript dataset. It achieves the following results on the evaluation set:
- Loss: 0.1219
- Precision: 0.9014
- Recall: 0.9308
- F1: 0.9159
- Accuracy: 0.9658
Model description
More information needed
Intended uses & limitations
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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 |
---|---|---|---|---|---|---|---|
No log | 1.0 | 298 | 0.1208 | 0.9016 | 0.8988 | 0.9002 | 0.9604 |
0.118 | 2.0 | 596 | 0.1152 | 0.9016 | 0.9210 | 0.9112 | 0.9645 |
0.118 | 3.0 | 894 | 0.1219 | 0.9014 | 0.9308 | 0.9159 | 0.9658 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
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Evaluation results
- Precision on skriptself-reported0.901
- Recall on skriptself-reported0.931
- F1 on skriptself-reported0.916
- Accuracy on skriptself-reported0.966