---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-large-uncased-v10-ES-ner
  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. -->

# bert-large-uncased-v10-ES-ner

This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5047
- Precision: 0.6503
- Recall: 0.7107
- F1: 0.6792
- Accuracy: 0.9157

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4056        | 1.75  | 500  | 0.3016          | 0.6128    | 0.6736 | 0.6417 | 0.9118   |
| 0.1603        | 3.5   | 1000 | 0.3561          | 0.6350    | 0.6756 | 0.6547 | 0.9105   |
| 0.0727        | 5.24  | 1500 | 0.4252          | 0.6654    | 0.7149 | 0.6892 | 0.9163   |
| 0.0341        | 6.99  | 2000 | 0.4574          | 0.6542    | 0.6839 | 0.6687 | 0.9124   |
| 0.0168        | 8.74  | 2500 | 0.5047          | 0.6503    | 0.7107 | 0.6792 | 0.9157   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2