metadata
library_name: transformers
base_model: allenai/biomed_roberta_base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BioMedRoBERTa-finetuned-ner-pablo-just-classifier
results: []
BioMedRoBERTa-finetuned-ner-pablo-just-classifier
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: 0.1276
- Precision: 0.6818
- Recall: 0.7031
- F1: 0.6923
- Accuracy: 0.9672
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: 0.1
- train_batch_size: 2
- eval_batch_size: 2
- 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 |
|---|---|---|---|---|---|---|---|
| 0.7191 | 1.0 | 2509 | 0.5248 | 0.5127 | 0.6334 | 0.5667 | 0.9486 |
| 0.5382 | 2.0 | 5018 | 0.4280 | 0.5378 | 0.6500 | 0.5886 | 0.9556 |
| 0.3968 | 3.0 | 7527 | 0.3095 | 0.4997 | 0.6714 | 0.5730 | 0.9531 |
| 0.2528 | 4.0 | 10036 | 0.1872 | 0.5631 | 0.6850 | 0.6181 | 0.9599 |
| 0.1541 | 5.0 | 12545 | 0.1276 | 0.6818 | 0.7031 | 0.6923 | 0.9672 |
Framework versions
- Transformers 4.44.1
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1