pytorch tensorboard bert token-classification transformers generated_from_trainer license:apache-2.0 model-index autotrain_compatible
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: NER_EHR_Spanish_model_Mulitlingual_BERT
  results: []
---

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# NER_EHR_Spanish_model_Mulitlingual_BERT

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the DisTEMIST shared task 2022 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2603
- Precision: 0.5637
- Recall: 0.5801
- F1: 0.5718
- Accuracy: 0.9534

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 71   | 0.2060          | 0.5017    | 0.5540 | 0.5266 | 0.9496   |
| No log        | 2.0   | 142  | 0.2163          | 0.5363    | 0.5433 | 0.5398 | 0.9495   |
| No log        | 3.0   | 213  | 0.2245          | 0.5521    | 0.5356 | 0.5438 | 0.9514   |
| No log        | 4.0   | 284  | 0.2453          | 0.5668    | 0.5985 | 0.5822 | 0.9522   |
| No log        | 5.0   | 355  | 0.2433          | 0.5657    | 0.5579 | 0.5617 | 0.9530   |
| No log        | 6.0   | 426  | 0.2553          | 0.5762    | 0.5762 | 0.5762 | 0.9536   |
| No log        | 7.0   | 497  | 0.2603          | 0.5637    | 0.5801 | 0.5718 | 0.9534   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.2.0
- Tokenizers 0.12.1
