---
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-0.0002-32
  results: []
---

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# BioMedRoBERTa-finetuned-valid-testing-0.0002-32

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: 0.0879
- Precision: 0.8178
- Recall: 0.8292
- F1: 0.8235
- Accuracy: 0.9763

## 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: 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  | 0.1001          | 0.7504    | 0.7779 | 0.7639 | 0.9695   |
| No log        | 2.0   | 418  | 0.0776          | 0.8208    | 0.8153 | 0.8180 | 0.9771   |
| 0.2051        | 3.0   | 627  | 0.0812          | 0.8026    | 0.8140 | 0.8083 | 0.9725   |
| 0.2051        | 4.0   | 836  | 0.0850          | 0.7953    | 0.8254 | 0.8101 | 0.9758   |
| 0.0355        | 5.0   | 1045 | 0.0879          | 0.8178    | 0.8292 | 0.8235 | 0.9763   |


### Framework versions

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