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

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

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: 0.0985
- Precision: 0.8190
- Recall: 0.8095
- F1: 0.8142
- Accuracy: 0.9779

## 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: 3e-05
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0864        | 1.0   | 2509  | 0.0915          | 0.8408    | 0.7476 | 0.7915 | 0.9753   |
| 0.0616        | 2.0   | 5018  | 0.0766          | 0.8116    | 0.7911 | 0.8012 | 0.9782   |
| 0.0439        | 3.0   | 7527  | 0.0838          | 0.8132    | 0.8024 | 0.8078 | 0.9776   |
| 0.0338        | 4.0   | 10036 | 0.0891          | 0.8207    | 0.8030 | 0.8118 | 0.9775   |
| 0.0268        | 5.0   | 12545 | 0.0985          | 0.8190    | 0.8095 | 0.8142 | 0.9779   |


### Framework versions

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