---
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-0.0001-16
  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-0.0001-16

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: 0.0924
- Precision: 0.8156
- Recall: 0.8242
- F1: 0.8199
- Accuracy: 0.9768

## 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: 0.0001
- 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  | 0.0960          | 0.7712    | 0.8074 | 0.7889 | 0.9706   |
| 0.3056        | 2.0   | 834  | 0.0765          | 0.8187    | 0.8211 | 0.8199 | 0.9766   |
| 0.0587        | 3.0   | 1251 | 0.0784          | 0.8116    | 0.8104 | 0.8110 | 0.9744   |
| 0.0401        | 4.0   | 1668 | 0.0877          | 0.8027    | 0.8316 | 0.8169 | 0.9758   |
| 0.027         | 5.0   | 2085 | 0.0924          | 0.8156    | 0.8242 | 0.8199 | 0.9768   |


### Framework versions

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