BioMedRoBERTa-full-finetuned-ner-pablo
This model is a fine-tuned version of allenai/biomed_roberta_base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0739
- Precision: 0.8048
- Recall: 0.7953
- F1: 0.8000
- Accuracy: 0.9775
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 231 | 0.0877 | 0.7475 | 0.7719 | 0.7595 | 0.9733 |
No log | 2.0 | 462 | 0.0766 | 0.7797 | 0.7900 | 0.7848 | 0.9756 |
0.2598 | 3.0 | 693 | 0.0730 | 0.8042 | 0.7949 | 0.7995 | 0.9774 |
0.2598 | 4.0 | 924 | 0.0739 | 0.8048 | 0.7953 | 0.8000 | 0.9775 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Downloads last month
- 179
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for pabRomero/BioMedRoBERTa-full-finetuned-ner-pablo
Base model
allenai/biomed_roberta_base
Quantized
this model