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---
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-0.00005-32
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# BioMedRoBERTa-finetuned-valid-testing-0.00005-32
This model is a fine-tuned version of [allenai/biomed_roberta_base](https://huggingface.co/allenai/biomed_roberta_base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0815
- Precision: 0.8113
- Recall: 0.8227
- F1: 0.8170
- Accuracy: 0.9767
## 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: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 209 | 0.1000 | 0.7636 | 0.7646 | 0.7641 | 0.9705 |
| No log | 2.0 | 418 | 0.0758 | 0.8278 | 0.8160 | 0.8219 | 0.9776 |
| 0.2839 | 3.0 | 627 | 0.0788 | 0.7928 | 0.8070 | 0.7999 | 0.9745 |
| 0.2839 | 4.0 | 836 | 0.0807 | 0.8028 | 0.8270 | 0.8148 | 0.9764 |
| 0.0449 | 5.0 | 1045 | 0.0815 | 0.8113 | 0.8227 | 0.8170 | 0.9767 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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