---
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-0.00005-16
  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-0.00005-16

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: 0.0868
- Precision: 0.8162
- Recall: 0.8225
- F1: 0.8194
- Accuracy: 0.9766

## 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: 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  | 0.1006          | 0.7400    | 0.7857 | 0.7622 | 0.9694   |
| 0.3728        | 2.0   | 834  | 0.0739          | 0.8268    | 0.8092 | 0.8179 | 0.9778   |
| 0.0615        | 3.0   | 1251 | 0.0800          | 0.7988    | 0.8101 | 0.8044 | 0.9734   |
| 0.0449        | 4.0   | 1668 | 0.0843          | 0.8111    | 0.8214 | 0.8162 | 0.9763   |
| 0.0325        | 5.0   | 2085 | 0.0868          | 0.8162    | 0.8225 | 0.8194 | 0.9766   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1