roberta-large-finetuned-ner-finetuned-ner
This model is a fine-tuned version of romainlhardy/roberta-large-finetuned-ner on surrey-nlp/PLOD-filtered dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.1264
- eval_precision: 0.9593
- eval_recall: 0.9473
- eval_f1: 0.9533
- eval_accuracy: 0.9488
- eval_runtime: 588.3236
- eval_samples_per_second: 41.032
- eval_steps_per_second: 10.258
- epoch: 0.59
- step: 16493
label description
['B-O', 'B-AC', 'I-AC', 'B-LF', 'I-LF']
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: 2
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
romainlhardy/roberta-large-finetuned-ner