---
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: 0.1220
- Precision: 0.6776
- Recall: 0.6935
- F1: 0.6854
- Accuracy: 0.9668

## 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: 512
- eval_batch_size: 512
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 23   | 0.2632          | 0.5303    | 0.6291 | 0.5755 | 0.9548   |
| No log        | 2.0   | 46   | 0.1581          | 0.6207    | 0.6712 | 0.6450 | 0.9630   |
| No log        | 3.0   | 69   | 0.1357          | 0.6494    | 0.6856 | 0.6670 | 0.9652   |
| No log        | 4.0   | 92   | 0.1245          | 0.6658    | 0.6919 | 0.6786 | 0.9664   |
| No log        | 5.0   | 115  | 0.1220          | 0.6776    | 0.6935 | 0.6854 | 0.9668   |


### Framework versions

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