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
results: []
BioMedRoBERTa-finetuned-valid-testing
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: 0.0920
- Precision: 0.8179
- Recall: 0.8236
- F1: 0.8207
- Accuracy: 0.9760
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 16
- 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 | 417 | 0.1029 | 0.7906 | 0.7974 | 0.7940 | 0.9711 |
| 0.256 | 2.0 | 834 | 0.0807 | 0.8322 | 0.8077 | 0.8198 | 0.9772 |
| 0.0658 | 3.0 | 1251 | 0.0862 | 0.7913 | 0.8086 | 0.7999 | 0.9712 |
| 0.0448 | 4.0 | 1668 | 0.0871 | 0.8132 | 0.8151 | 0.8142 | 0.9768 |
| 0.0288 | 5.0 | 2085 | 0.0920 | 0.8179 | 0.8236 | 0.8207 | 0.9760 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1