---
base_model: dccuchile/bert-base-spanish-wwm-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: FNST_trad_l
  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. -->

# FNST_trad_l

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: 4.0024
- Accuracy: 0.5983
- F1: 0.5955

## 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: 1e-06
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 42

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 1.127         | 1.0   | 2000  | 1.1060          | 0.5133   | 0.4590 |
| 0.9786        | 2.0   | 4000  | 1.0075          | 0.5642   | 0.5524 |
| 0.9072        | 3.0   | 6000  | 0.9958          | 0.5733   | 0.5697 |
| 0.869         | 4.0   | 8000  | 0.9776          | 0.5917   | 0.5957 |
| 0.8243        | 5.0   | 10000 | 0.9760          | 0.5817   | 0.5860 |
| 0.7659        | 6.0   | 12000 | 0.9826          | 0.595    | 0.5993 |
| 0.7414        | 7.0   | 14000 | 1.0055          | 0.5933   | 0.6001 |
| 0.7023        | 8.0   | 16000 | 1.0113          | 0.5908   | 0.5959 |
| 0.6745        | 9.0   | 18000 | 1.0527          | 0.5933   | 0.5949 |
| 0.6161        | 10.0  | 20000 | 1.1227          | 0.5883   | 0.5920 |
| 0.5863        | 11.0  | 22000 | 1.1571          | 0.5883   | 0.5896 |
| 0.5406        | 12.0  | 24000 | 1.1883          | 0.5908   | 0.5954 |
| 0.5185        | 13.0  | 26000 | 1.2686          | 0.5917   | 0.5957 |
| 0.4796        | 14.0  | 28000 | 1.3313          | 0.5992   | 0.6067 |
| 0.4379        | 15.0  | 30000 | 1.4234          | 0.595    | 0.5970 |
| 0.3883        | 16.0  | 32000 | 1.5582          | 0.5958   | 0.5994 |
| 0.3934        | 17.0  | 34000 | 1.6591          | 0.595    | 0.6012 |
| 0.359         | 18.0  | 36000 | 1.8129          | 0.595    | 0.6011 |
| 0.3249        | 19.0  | 38000 | 1.9811          | 0.5917   | 0.5966 |
| 0.2954        | 20.0  | 40000 | 2.1860          | 0.5858   | 0.5901 |
| 0.3064        | 21.0  | 42000 | 2.2548          | 0.5858   | 0.5904 |
| 0.2844        | 22.0  | 44000 | 2.3557          | 0.6      | 0.6045 |
| 0.2471        | 23.0  | 46000 | 2.5137          | 0.6017   | 0.6033 |
| 0.2432        | 24.0  | 48000 | 2.6458          | 0.5992   | 0.6035 |
| 0.2247        | 25.0  | 50000 | 2.8667          | 0.5983   | 0.6026 |
| 0.213         | 26.0  | 52000 | 2.8895          | 0.6042   | 0.6088 |
| 0.1792        | 27.0  | 54000 | 3.0338          | 0.6008   | 0.6062 |
| 0.1723        | 28.0  | 56000 | 3.1234          | 0.5975   | 0.6008 |
| 0.1562        | 29.0  | 58000 | 3.2822          | 0.5942   | 0.5992 |
| 0.1437        | 30.0  | 60000 | 3.3156          | 0.6067   | 0.6096 |
| 0.151         | 31.0  | 62000 | 3.3923          | 0.6075   | 0.6098 |
| 0.1446        | 32.0  | 64000 | 3.4562          | 0.6058   | 0.6084 |
| 0.109         | 33.0  | 66000 | 3.6100          | 0.6017   | 0.6038 |
| 0.1138        | 34.0  | 68000 | 3.6468          | 0.6083   | 0.6078 |
| 0.1068        | 35.0  | 70000 | 3.6758          | 0.5967   | 0.6004 |
| 0.1133        | 36.0  | 72000 | 3.7340          | 0.6033   | 0.6025 |
| 0.0865        | 37.0  | 74000 | 3.7666          | 0.6083   | 0.6079 |
| 0.0936        | 38.0  | 76000 | 3.8650          | 0.6058   | 0.6073 |
| 0.0957        | 39.0  | 78000 | 3.9209          | 0.605    | 0.6025 |
| 0.1027        | 40.0  | 80000 | 3.9211          | 0.6058   | 0.6054 |
| 0.0828        | 41.0  | 82000 | 4.0124          | 0.6058   | 0.6009 |
| 0.0742        | 42.0  | 84000 | 4.0024          | 0.5983   | 0.5955 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1