NER-finetuning-xml-roberta-prostata
This model is a fine-tuned version of FacebookAI/xlm-roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0304
- Precision: 0.9616
- Recall: 0.9635
- F1: 0.9626
- Accuracy: 0.9936
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 98 | 0.0950 | 0.8240 | 0.9120 | 0.8657 | 0.9754 |
No log | 2.0 | 196 | 0.0402 | 0.9401 | 0.9540 | 0.9470 | 0.9919 |
No log | 3.0 | 294 | 0.0275 | 0.9587 | 0.9625 | 0.9606 | 0.9938 |
No log | 4.0 | 392 | 0.0273 | 0.9629 | 0.9754 | 0.9691 | 0.9942 |
No log | 5.0 | 490 | 0.0242 | 0.9716 | 0.9761 | 0.9738 | 0.9960 |
0.1436 | 6.0 | 588 | 0.0255 | 0.9728 | 0.9735 | 0.9731 | 0.9959 |
0.1436 | 7.0 | 686 | 0.0235 | 0.9773 | 0.9761 | 0.9767 | 0.9960 |
0.1436 | 8.0 | 784 | 0.0223 | 0.9761 | 0.9767 | 0.9764 | 0.9961 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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Base model
FacebookAI/xlm-roberta-large