metadata
library_name: transformers
base_model: allenai/biomed_roberta_base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BioMedRoBERTa-finetuned-valid-testing-0.0001-32
results: []
BioMedRoBERTa-finetuned-valid-testing-0.0001-32
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: 0.0835
- Precision: 0.8178
- Recall: 0.8281
- F1: 0.8229
- Accuracy: 0.9769
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: 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: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 209 | 0.0882 | 0.7639 | 0.7805 | 0.7721 | 0.9718 |
| No log | 2.0 | 418 | 0.0735 | 0.8259 | 0.8222 | 0.8240 | 0.9775 |
| 0.2568 | 3.0 | 627 | 0.0779 | 0.8060 | 0.8110 | 0.8085 | 0.9746 |
| 0.2568 | 4.0 | 836 | 0.0815 | 0.8062 | 0.8245 | 0.8152 | 0.9768 |
| 0.0375 | 5.0 | 1045 | 0.0835 | 0.8178 | 0.8281 | 0.8229 | 0.9769 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1