---
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: 0.1228
- Precision: 0.6701
- Recall: 0.6809
- F1: 0.6754
- Accuracy: 0.9657

## 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: 0.01
- train_batch_size: 512
- eval_batch_size: 512
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 2048
- 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        | 0.9697 | 16   | 0.2938          | 0.4425    | 0.5130 | 0.4751 | 0.9361   |
| No log        | 2.0    | 33   | 0.1815          | 0.5546    | 0.5873 | 0.5705 | 0.9535   |
| No log        | 2.9697 | 49   | 0.1617          | 0.5838    | 0.6189 | 0.6008 | 0.9575   |
| No log        | 4.0    | 66   | 0.1482          | 0.6070    | 0.6396 | 0.6229 | 0.9602   |
| No log        | 4.9697 | 82   | 0.1340          | 0.6465    | 0.6563 | 0.6513 | 0.9633   |
| No log        | 6.0    | 99   | 0.1306          | 0.6561    | 0.6638 | 0.6599 | 0.9641   |
| No log        | 6.9697 | 115  | 0.1290          | 0.6569    | 0.6705 | 0.6636 | 0.9645   |
| No log        | 8.0    | 132  | 0.1246          | 0.6664    | 0.6794 | 0.6728 | 0.9654   |
| No log        | 8.9697 | 148  | 0.1230          | 0.6699    | 0.6793 | 0.6745 | 0.9656   |
| No log        | 9.6970 | 160  | 0.1228          | 0.6701    | 0.6809 | 0.6754 | 0.9657   |


### Framework versions

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