---
library_name: transformers
base_model: allenai/biomed_roberta_base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BioMedRoBERTa-finetuned-ner-pablo-just-classifier
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# BioMedRoBERTa-finetuned-ner-pablo-just-classifier

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: 0.1276
- Precision: 0.6818
- Recall: 0.7031
- F1: 0.6923
- Accuracy: 0.9672

## 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: 0.1
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.7191        | 1.0   | 2509  | 0.5248          | 0.5127    | 0.6334 | 0.5667 | 0.9486   |
| 0.5382        | 2.0   | 5018  | 0.4280          | 0.5378    | 0.6500 | 0.5886 | 0.9556   |
| 0.3968        | 3.0   | 7527  | 0.3095          | 0.4997    | 0.6714 | 0.5730 | 0.9531   |
| 0.2528        | 4.0   | 10036 | 0.1872          | 0.5631    | 0.6850 | 0.6181 | 0.9599   |
| 0.1541        | 5.0   | 12545 | 0.1276          | 0.6818    | 0.7031 | 0.6923 | 0.9672   |


### Framework versions

- Transformers 4.44.1
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1