---
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: 0.1094
- Precision: 0.8151
- Recall: 0.7999
- F1: 0.8074
- Accuracy: 0.9737

## 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: 128
- eval_batch_size: 128
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3008        | 1.0   | 613  | 0.0937          | 0.8042    | 0.7705 | 0.7870 | 0.9727   |
| 0.0799        | 2.0   | 1226 | 0.0873          | 0.8103    | 0.7936 | 0.8019 | 0.9744   |
| 0.0649        | 3.0   | 1839 | 0.0888          | 0.8179    | 0.7930 | 0.8053 | 0.9748   |
| 0.053         | 4.0   | 2452 | 0.0966          | 0.8082    | 0.7978 | 0.8029 | 0.9732   |
| 0.0321        | 5.0   | 3065 | 0.1094          | 0.8151    | 0.7999 | 0.8074 | 0.9737   |


### Framework versions

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