---
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: 0.0951
- Precision: 0.8139
- Recall: 0.8085
- F1: 0.8112
- Accuracy: 0.9769

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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        | 0.9970 | 252  | 0.0910          | 0.7348    | 0.7922 | 0.7624 | 0.9723   |
| 0.19          | 1.9980 | 505  | 0.0808          | 0.8030    | 0.7908 | 0.7969 | 0.9768   |
| 0.19          | 2.9990 | 758  | 0.0802          | 0.8125    | 0.7932 | 0.8028 | 0.9768   |
| 0.0433        | 4.0    | 1011 | 0.0865          | 0.8131    | 0.8103 | 0.8117 | 0.9772   |
| 0.0433        | 4.9852 | 1260 | 0.0951          | 0.8139    | 0.8085 | 0.8112 | 0.9769   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1