---
library_name: transformers
license: mit
base_model: emilyalsentzer/Bio_ClinicalBERT
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
should probably proofread and complete it, then remove this comment. -->

# BioMedRoBERTa-finetuned-ner-pablo-just-classifier

This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1150
- Precision: 0.6869
- Recall: 0.7076
- F1: 0.6971
- Accuracy: 0.9677

## 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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 0.9655 | 14   | 0.3729          | 0.4205    | 0.6119 | 0.4985 | 0.9430   |
| No log        | 2.0    | 29   | 0.2544          | 0.5272    | 0.6683 | 0.5894 | 0.9574   |
| No log        | 2.9655 | 43   | 0.2117          | 0.5702    | 0.6884 | 0.6238 | 0.9604   |
| No log        | 4.0    | 58   | 0.1747          | 0.5934    | 0.7001 | 0.6424 | 0.9628   |
| No log        | 4.9655 | 72   | 0.1420          | 0.6280    | 0.6827 | 0.6542 | 0.9642   |
| No log        | 6.0    | 87   | 0.1287          | 0.6639    | 0.7033 | 0.6830 | 0.9667   |
| No log        | 6.9655 | 101  | 0.1309          | 0.6471    | 0.7009 | 0.6729 | 0.9654   |
| No log        | 8.0    | 116  | 0.1260          | 0.6349    | 0.7199 | 0.6748 | 0.9652   |
| No log        | 8.9655 | 130  | 0.1159          | 0.6621    | 0.7118 | 0.6860 | 0.9670   |
| No log        | 9.6552 | 140  | 0.1150          | 0.6869    | 0.7076 | 0.6971 | 0.9677   |


### Framework versions

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