---
library_name: transformers
base_model: dccuchile/bert-base-spanish-wwm-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: super_cnll_2e
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# super_cnll_2e

This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1780
- Precision: 0.5906
- Recall: 0.6667
- F1: 0.6264
- Accuracy: 0.9446

## 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 63   | 0.2281          | 0.5242    | 0.5710 | 0.5466 | 0.9322   |
| No log        | 2.0   | 126  | 0.1780          | 0.5906    | 0.6667 | 0.6264 | 0.9446   |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cpu
- Datasets 4.0.0
- Tokenizers 0.22.2