roberta-large-finetuned-ner-finetuned-ner
This model is a fine-tuned version of romainlhardy/roberta-large-finetuned-ner on the plod-cw dataset. It achieves the following results on the evaluation set:
- Loss: 0.2327
- Precision: 0.9597
- Recall: 0.9503
- F1: 0.9550
- Accuracy: 0.9495
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: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
romainlhardy/roberta-large-finetuned-nerEvaluation results
- Precision on plod-cwvalidation set self-reported0.960
- Recall on plod-cwvalidation set self-reported0.950
- F1 on plod-cwvalidation set self-reported0.955
- Accuracy on plod-cwvalidation set self-reported0.949