---
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
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# 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