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---
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
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