metadata
library_name: transformers
base_model: allenai/biomed_roberta_base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BioMedRoBERTa-full-finetuned-ner-pablo
results: []
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: 0.1094
- Precision: 0.8151
- Recall: 0.7999
- F1: 0.8074
- Accuracy: 0.9737
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: 0.0001
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.3008 | 1.0 | 613 | 0.0937 | 0.8042 | 0.7705 | 0.7870 | 0.9727 |
| 0.0799 | 2.0 | 1226 | 0.0873 | 0.8103 | 0.7936 | 0.8019 | 0.9744 |
| 0.0649 | 3.0 | 1839 | 0.0888 | 0.8179 | 0.7930 | 0.8053 | 0.9748 |
| 0.053 | 4.0 | 2452 | 0.0966 | 0.8082 | 0.7978 | 0.8029 | 0.9732 |
| 0.0321 | 5.0 | 3065 | 0.1094 | 0.8151 | 0.7999 | 0.8074 | 0.9737 |
Framework versions
- Transformers 4.44.1
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1