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---
library_name: transformers
base_model: dccuchile/bert-base-spanish-wwm-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Neuria_BERT_Graficos_2025_02_05
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. -->
# Neuria_BERT_Graficos_2025_02_05
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: 0.3226
- Accuracy: 0.9634
## 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: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1144 | 1.0 | 29 | 0.5802 | 0.6707 |
| 0.527 | 2.0 | 58 | 0.6142 | 0.7561 |
| 0.2708 | 3.0 | 87 | 0.4024 | 0.8780 |
| 0.0954 | 4.0 | 116 | 0.4247 | 0.9024 |
| 0.0864 | 5.0 | 145 | 0.3698 | 0.9024 |
| 0.0146 | 6.0 | 174 | 0.4584 | 0.9146 |
| 0.0213 | 7.0 | 203 | 0.4625 | 0.9268 |
| 0.0267 | 8.0 | 232 | 0.3833 | 0.9268 |
| 0.0009 | 9.0 | 261 | 0.2960 | 0.9512 |
| 0.0007 | 10.0 | 290 | 0.2934 | 0.9512 |
| 0.0005 | 11.0 | 319 | 0.2940 | 0.9634 |
| 0.0005 | 12.0 | 348 | 0.3021 | 0.9634 |
| 0.0004 | 13.0 | 377 | 0.3062 | 0.9634 |
| 0.0004 | 14.0 | 406 | 0.3084 | 0.9634 |
| 0.0004 | 15.0 | 435 | 0.3158 | 0.9634 |
| 0.0003 | 16.0 | 464 | 0.3173 | 0.9634 |
| 0.0003 | 17.0 | 493 | 0.3146 | 0.9634 |
| 0.0003 | 18.0 | 522 | 0.3169 | 0.9634 |
| 0.0003 | 19.0 | 551 | 0.3215 | 0.9634 |
| 0.0002 | 20.0 | 580 | 0.3226 | 0.9634 |
### Framework versions
- Transformers 4.44.1
- Pytorch 2.4.1
- Datasets 2.19.1
- Tokenizers 0.19.1
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